Pipeline run
9eb27c7e-c22e-4e2c-8c17-6c24aff1efe1
Client output enrichment
v2 Skill cluster · Nature of work · AI index · Tech stack maturity · Evidence · KRA descriptionvocab breakdown (legacy)
Signals
Post-classification
Captured for admin review
1 POST /skills/extract-from-jd
2 POST /skills/extract-details
3 POST /skills/final-role-output
Data Engineer
CASE Aslug: data-engineer · id: 2 · source: db
Exact alias hit on data-engineer (1.0) — no other alias at this confidence; skill_top data-engineer 0.50 does not contradict
Resolution:
in_db
— role exists in library; skill↔dim and role↔dim links saved when applicable.
Job description
Job Description------------------------------------------- Work Mode: WFO Start Date: Immediate Description We are looking for a Senior GCP Data Engineer who's confident, curious, and straightforward, a great fit for our empowering and driven culture. The candidate’s determination and clear communication will make our cloud-based solutions sharp and easy to understand. Candidates need to solve problems effortlessly and effectively in the cloud. Join us if you're excited to be part of a team that values clarity, confidence, and getting things done through cloud technology. Responsibilities: ● Designing and developing complex and large-scale data structures and pipelines to organize, collect, and standardize data to generate insights and address reporting needs ● Writing complex ETL (Extract / Transform / Load) processes, designs database systems and develops tools for real-time and offline analytic processing ● Developing frameworks, standards & reference material for architecture and associated products ● Designing data marts and data models to support Data Science and other internal customers. ● Behaving as mentor to junior team members to provide technical advice ● Applying knowledge of gcp-data tools and products to consult and advise on additional efforts across multiple domains spanning broader enterprise ● Collaborating with data science team to transform data and integrate algorithms and models into highly available, production systems ● Using in-depth knowledge on Hadoop architecture and HDFS commands and experience designing & optimizing queries to build scalable, modular, and efficient data pipelines ● Using advanced programming skills in Python, Java, PySpark, or any of the major languages to build robust data pipelines and dynamic systems ● Integrating data from a variety of sources, assuring that they adhere to data quality and accessibility standards ● Experimenting with available tools and advice on new tools in order to determine optimal solution given the requirements dictated by the model/use case Requirements: ● 5+ years Data Engineering experience ● 5+ years PySpark (Spark/Scala) ● 3+ years advanced knowledge in Hadoop architecture, HDFS commands and experience designing & optimising queries against data in the HDFS environment ● 2+ years' experience with Google Cloud Platform ( GCP ) ● Experience with bash shell scripts, UNIX utilities & UNIX Commands ● Experience building and implementing data transformation and processing solutions ● Advanced knowledge in Java, Python, Hive, Cassandra, Pig, MySQL or NoSQL or similar ● If you are passionate about DevOps and GCP, and if you thrive in a collaborative and fast-paced environment ● You like to solve puzzles and figure things out, how they work, how they operate etc. ● You thrive in an environment that constantly demands you to learn.
Skills from this JD
Each row merges API 1 extraction, API 2 library match / v3 orchestration (dimensions + locked dims), and API 3 persistence tags.
Aliases — catalog
- Google Cloud Platform (CANONICAL) primary
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Platform
- Sub-category
- Cloud Platform
- Vendor
- License
- other_open
- Year introduced
- 2008
- Confidence
- 0.99
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: GCP appears in many cloud-engineering job descriptions alongside AWS/Azure, and Google continues expanding managed services and certifications, indicating broad hiring demand rather than niche use.
Skill profile (library / DB)
- Skill nature
- PLATFORM
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 9
- Sub-category id
- 46
- Extractable
- True
- Also category
- False
Dimensions (API 2 worklist)
-
Cloud & Hosting Providers Catalog dimension db id 414
Library dimension (catalog)
Roles linked in library: PHP Backend Developer
-
Cloud Provider Platforms Catalog dimension db id 131
Library dimension (catalog)
Roles linked in library: Cloud Architect, Cloud Security Engineer
-
Cloud Security Posture Tools Catalog dimension db id 64
Library dimension (catalog)
Roles linked in library: Cloud Security Engineer, Cyber Security Engineer
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
Cloud & Hosting Providers
cloud-hosting-providers
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Cloud Provider Platforms
cloud-provider-platforms
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Cloud Security Posture Tools
cloud-security-posture-tools
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
Aliases — catalog
- Python (CANONICAL) primary
- Python 2 (VERSION)
- Python 2.x (VERSION)
- Python 3 (VERSION)
- Python 3.10 (VERSION)
- Python 3.11 (VERSION)
- Python 3.12 (VERSION)
- Python 3.x (VERSION)
- py (VERSION)
- py2 (VERSION)
- py3 (VERSION)
- python 3 (VERSION)
- python 3.x (VERSION)
- python2 (VERSION)
- python3 (VERSION)
- python3.x (VERSION)
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Language
- Sub-category
- Programming Language
- Vendor
- PSF
- License
- mit
- Year introduced
- 1991
- Confidence
- 0.99
- Version strategy
- SEPARATE_ENTITY
- Version tag
- 3
Maturity reasoning: Python appears in a very high volume of job descriptions across data, backend, automation, and ML roles, and remains a default hiring-pipeline language on major job boards and tech stacks.
Skill profile (library / DB)
- Skill nature
- LANGUAGE
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 6
- Sub-category id
- 96
- Extractable
- True
- Also category
- False
Dimensions (API 2 worklist)
-
Cloud Security Scripting & DSL Languages Catalog dimension db id 248
Library dimension (catalog)
Roles linked in library: Cloud Security Engineer
-
Programming Languages Catalog dimension db id 1
Library dimension (catalog)
Roles linked in library: Backend Developer, Fullstack Developer
-
Programming Languages and Scripting Catalog dimension db id 59
Library dimension (catalog)
Roles linked in library: Cyber Security Engineer
-
Programming Languages for Data Work Catalog dimension db id 21
Library dimension (catalog)
Roles linked in library: Data Engineer
-
Programming Languages for ML Systems Catalog dimension db id 39
Library dimension (catalog)
Roles linked in library: ML Engineer, MLOps Engineer
-
Programming Languages for XR Catalog dimension db id 97
Library dimension (catalog)
Roles linked in library: AR/VR Engineer
-
Python Programming Catalog dimension db id 290
Library dimension (catalog)
Roles linked in library: Python Backend Developer
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
Cloud Security Scripting & DSL Languages
cloud-security-scripting-dsl-languages
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Programming Languages
programming-languages
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Programming Languages and Scripting
programming-languages-and-scripting
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Programming Languages for Data Work
programming-languages-for-data-work
|
✓ | ✓ | Existing dimension (library) · Role↔dimension saved |
|
Programming Languages for ML Systems
programming-languages-for-ml-systems
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Programming Languages for XR
programming-languages-for-xr
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Python Programming
python-programming
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
Aliases — catalog
- Java (CANONICAL) primary
- JDK (VERSION)
- JDK 10 (VERSION)
- JDK 11 (VERSION)
- JDK 12 (VERSION)
- JDK 13 (VERSION)
- JDK 14 (VERSION)
- JDK 15 (VERSION)
- JDK 16 (VERSION)
- JDK 17 (VERSION)
- JDK 18 (VERSION)
- JDK 19 (VERSION)
- JDK 20 (VERSION)
- JDK 21 (VERSION)
- JDK 5 (VERSION)
- JDK 6 (VERSION)
- JDK 7 (VERSION)
- JDK 8 (VERSION)
- JDK 9 (VERSION)
- Java 1.0 (VERSION)
- Java 1.1 (VERSION)
- Java 1.2 (VERSION)
- Java 1.3 (VERSION)
- Java 1.4 (VERSION)
- Java 1.5 (VERSION)
- Java 1.6 (VERSION)
- Java 1.7 (VERSION)
- Java 1.8 (VERSION)
- Java 10 (VERSION)
- Java 11 (VERSION)
- Java 12 (VERSION)
- Java 13 (VERSION)
- Java 14 (VERSION)
- Java 15 (VERSION)
- Java 16 (VERSION)
- Java 17 (VERSION)
- Java 18 (VERSION)
- Java 19 (VERSION)
- Java 20 (VERSION)
- Java 21 (VERSION)
- Java 5 (VERSION)
- Java 6 (VERSION)
- Java 7 (VERSION)
- Java 8 (VERSION)
- Java 9 (VERSION)
- Java11 (VERSION)
- Java17 (VERSION)
- Java21 (VERSION)
- Java8 (VERSION)
- OpenJDK 11 (VERSION)
- OpenJDK 17 (VERSION)
- OpenJDK 21 (VERSION)
- OpenJDK 8 (VERSION)
- java 11 (VERSION)
- java 17 (VERSION)
- java 21 (VERSION)
- java 4 (VERSION)
- java 5 (VERSION)
- java 6 (VERSION)
- java 7 (VERSION)
- java 8 (VERSION)
- java lts (VERSION)
- java-11 (VERSION)
- java-17 (VERSION)
- java-21 (VERSION)
- java-4 (VERSION)
- java-5 (VERSION)
- java-6 (VERSION)
- java-7 (VERSION)
- java-8 (VERSION)
- java11 (VERSION)
- java17 (VERSION)
- java21 (VERSION)
- java4 (VERSION)
- java5 (VERSION)
- java6 (VERSION)
- java7 (VERSION)
- java8 (VERSION)
- jdk 11 (VERSION)
- jdk 17 (VERSION)
- jdk 21 (VERSION)
- jdk 4 (VERSION)
- jdk 5 (VERSION)
- jdk 6 (VERSION)
- jdk 7 (VERSION)
- jdk 8 (VERSION)
- jdk11 (VERSION)
- jdk17 (VERSION)
- jdk21 (VERSION)
- jdk4 (VERSION)
- jdk5 (VERSION)
- jdk6 (VERSION)
- jdk7 (VERSION)
- jdk8 (VERSION)
- jvm21 (VERSION)
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Language
- Sub-category
- Programming Language
- Vendor
- Oracle
- License
- other_open
- Year introduced
- 1995
- Confidence
- 0.99
- Version strategy
- SEPARATE_ENTITY
- Version tag
- 21
Maturity reasoning: Java is a hiring-pipeline staple with very high JD volume across enterprise backend, Android, and cloud roles; it remains widely supported by major vendors and frameworks like Spring.
Skill profile (library / DB)
- Skill nature
- LANGUAGE
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 6
- Sub-category id
- 96
- Extractable
- True
- Also category
- False
Dimensions (API 2 worklist)
-
Java Language and JVM Catalog dimension db id 279
Library dimension (catalog)
Roles linked in library: Java Backend Developer, Kotlin Backend Developer, Scala Backend Developer
-
Kotlin and Java Catalog dimension db id 161
Library dimension (catalog)
Roles linked in library: Android Developer
-
Native Mobile Languages Catalog dimension db id 274
Library dimension (catalog)
Roles linked in library: Native Mobile Developer
-
Pega Programming Languages & DSLs Catalog dimension db id 267
Library dimension (catalog)
Roles linked in library: Pega Developer
-
Programming Languages Catalog dimension db id 1
Library dimension (catalog)
Roles linked in library: Backend Developer, Fullstack Developer
-
Programming Languages for Data Work Catalog dimension db id 21
Library dimension (catalog)
Roles linked in library: Data Engineer
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
Java Language and JVM
java-language-and-jvm
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Kotlin and Java
kotlin-and-java
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Native Mobile Languages
native-mobile-languages
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Pega Programming Languages & DSLs
pega-programming-languages-dsls
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Programming Languages
programming-languages
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Programming Languages for Data Work
programming-languages-for-data-work
|
✓ | ✓ | Existing dimension (library) · Role↔dimension saved |
Aliases — catalog
- Apache Spark (CANONICAL)
- apache spark 3 (VERSION)
- spark (VERSION)
- spark 3 (VERSION)
- spark 3.x (VERSION)
- spark3 (VERSION)
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Framework
- Sub-category
- Distributed Data Processing Framework
- Vendor
- Apache Software Foundation
- License
- apache_2
- Year introduced
- 2010
- Confidence
- 0.94
- Version strategy
- SEPARATE_ENTITY
- Version tag
- 3.x
Maturity reasoning: Apache Spark appears in many data engineering JDs and remains a standard for distributed ETL/ELT; its GitHub and vendor ecosystem activity stay strong, with Databricks and cloud platforms still promoting it.
Skill profile (library / DB)
- Skill nature
- FRAMEWORK
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 5
- Sub-category id
- 1021
- Extractable
- True
- Also category
- False
Dimensions (API 2 worklist)
-
ETL and ELT Tooling Catalog dimension db id 24
Library dimension (catalog)
Roles linked in library: Data Engineer
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
ETL and ELT Tooling
etl-and-elt-tooling
|
— | — |
Skipped — no persistable v3 meta for new skill
skill_not_in_db_v3_proposed
|
Aliases — catalog
- Apache Spark (CANONICAL)
- apache spark 3 (VERSION)
- spark (VERSION)
- spark 3 (VERSION)
- spark 3.x (VERSION)
- spark3 (VERSION)
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Framework
- Sub-category
- Distributed Data Processing Framework
- Vendor
- Apache Software Foundation
- License
- apache_2
- Year introduced
- 2010
- Confidence
- 0.94
- Version strategy
- SEPARATE_ENTITY
- Version tag
- 3.x
Maturity reasoning: Apache Spark appears in many data engineering JDs and remains a standard for distributed ETL/ELT; its GitHub and vendor ecosystem activity stay strong, with Databricks and cloud platforms still promoting it.
Skill profile (library / DB)
- Skill nature
- FRAMEWORK
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 5
- Sub-category id
- 1021
- Extractable
- True
- Also category
- False
Dimensions (API 2 worklist)
-
ETL and ELT Tooling Catalog dimension db id 24
Library dimension (catalog)
Roles linked in library: Data Engineer
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
ETL and ELT Tooling
etl-and-elt-tooling
|
✓ | ✓ | Existing dimension (library) · Role↔dimension saved |
Aliases — catalog
- Scala (CANONICAL) primary
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Language
- Sub-category
- Programming Language
- Vendor
- EPFL
- License
- apache_2
- Year introduced
- 2004
- Confidence
- 0.99
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: Scala still appears in many backend/data engineering JDs, especially with Spark and Akka, and remains supported by major JVM ecosystems; it’s not a sunset technology.
Skill profile (library / DB)
- Skill nature
- LANGUAGE
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 6
- Sub-category id
- 96
- Extractable
- True
- Also category
- False
Dimensions (API 2 worklist)
-
Programming Languages for Data Work Catalog dimension db id 21
Library dimension (catalog)
Roles linked in library: Data Engineer
-
Programming Languages for ML Systems Catalog dimension db id 39
Library dimension (catalog)
Roles linked in library: ML Engineer, MLOps Engineer
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
Programming Languages for Data Work
programming-languages-for-data-work
|
✓ | ✓ | Existing dimension (library) · Role↔dimension saved |
|
Programming Languages for ML Systems
programming-languages-for-ml-systems
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
Aliases — catalog
- Hadoop (CANONICAL)
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Framework
- Sub-category
- Data Processing Framework
- Vendor
- Apache Software Foundation
- License
- apache_2
- Year introduced
- 2006
- Confidence
- 0.90
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: Job postings still mention Hadoop for legacy big-data stacks, but JD volume has fallen as Spark and cloud warehouses replaced MapReduce-era clusters.
Skill profile (library / DB)
- Skill nature
- FRAMEWORK
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 5
- Sub-category id
- 91
- Extractable
- True
- Also category
- False
Dimensions (API 2 worklist)
-
ETL and ELT Tooling Catalog dimension db id 24
Library dimension (catalog)
Roles linked in library: Data Engineer
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
ETL and ELT Tooling
etl-and-elt-tooling
|
✓ | ✓ | Existing dimension (library) · Role↔dimension saved |
Skill enrichment (orchestrator / LLM)
No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).
- Category
- Data Engineering Tools
- Sub-category
- general
- Skill nature
- TOOL
- Volatility
- MEDIUM
- Typical lifespan
- MULTI_YEAR
- Version strategy
- UNVERSIONED
Aliases — catalog
- Bash (VERSION)
- Bash 3.x (VERSION)
- Bash 4.x (VERSION)
- Bash 5.x (VERSION)
- GNU Bash (VERSION)
- bash (VERSION)
- bash 3 (VERSION)
- bash 3.x (VERSION)
- bash 4 (VERSION)
- bash 4.x (VERSION)
- bash 5 (VERSION)
- bash 5.x (VERSION)
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Language
- Sub-category
- Shell Language
- Vendor
- GNU Project
- License
- gpl_v3
- Year introduced
- 1989
- Confidence
- 0.99
- Version strategy
- SEPARATE_ENTITY
- Version tag
- 5.x
Maturity reasoning: Bash appears in many DevOps, SRE, and Linux admin job descriptions and remains the default shell on most Unix-like systems, with no vendor sunset or clear replacement in mainstream hiring.
Skill profile (library / DB)
- Skill nature
- LANGUAGE
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 6
- Sub-category id
- 238
- Extractable
- True
- Also category
- False
Dimensions (API 2 worklist)
-
Programming Languages and Scripting Catalog dimension db id 59
Library dimension (catalog)
Roles linked in library: Cyber Security Engineer
-
Programming Languages for Data Work Catalog dimension db id 21
Library dimension (catalog)
Roles linked in library: Data Engineer
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
Programming Languages and Scripting
programming-languages-and-scripting
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Programming Languages for Data Work
programming-languages-for-data-work
|
✓ | ✓ | Existing dimension (library) · Role↔dimension saved |
Skill enrichment (orchestrator / LLM)
No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).
- Category
- Operating Systems
- Sub-category
- general
- Skill nature
- PLATFORM
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Version strategy
- UNVERSIONED
Aliases — catalog
- Hive (CANONICAL) primary
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Datastore
- Sub-category
- Local Key Value Store
- Vendor
- Apache Software Foundation
- License
- apache_2
- Year introduced
- 2010
- Confidence
- 0.90
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: Hive appears in Flutter/mobile JDs and package docs, but JD volume is far below SQLite/Realm and it’s mainly used for local key-value storage in Flutter apps.
Skill profile (library / DB)
- Skill nature
- TOOL
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 3
- Sub-category id
- 2242
- Extractable
- True
- Also category
- False
Dimensions (API 2 worklist)
-
Local Persistence and Offline Behavior Catalog dimension db id 85
Library dimension (catalog)
Roles linked in library: Android Developer, Flutter Developer, Hybrid Mobile Developer, Native Mobile Developer, React Native Developer, iOS Developer
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
Local Persistence and Offline Behavior
local-persistence-and-offline-behavior
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
Aliases — catalog
- Cassandra (CANONICAL)
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Datastore
- Sub-category
- Wide Column Store
- Vendor
- Apache Software Foundation
- License
- apache_2
- Year introduced
- 2008
- Confidence
- 0.99
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: Apache Cassandra appears in many production data-platform JDs and is a common choice for high-write, distributed workloads; GitHub and vendor docs show sustained activity rather than sunset signals.
Skill profile (library / DB)
- Skill nature
- TOOL
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 3
- Sub-category id
- 31
- Extractable
- True
- Also category
- False
Dimensions (API 2 worklist)
-
Cloud Storage and Data Services Catalog dimension db id 144
Library dimension (catalog)
Roles linked in library: Cloud Architect
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
Cloud Storage and Data Services
cloud-storage-and-data-services
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
Skill enrichment (orchestrator / LLM)
No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).
- Category
- Data Engineering Tools
- Sub-category
- general
- Skill nature
- TOOL
- Volatility
- MEDIUM
- Typical lifespan
- MULTI_YEAR
- Version strategy
- UNVERSIONED
Aliases — catalog
- MySQL (CANONICAL) primary
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Datastore
- Sub-category
- Relational Database
- Vendor
- Oracle Corporation
- License
- gpl_v2
- Year introduced
- 1995
- Confidence
- 0.99
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: MySQL appears in a large share of backend/DB job descriptions and remains a standard managed offering across AWS RDS, Cloud SQL, and Azure Database, indicating broad hiring-pipeline demand.
Skill profile (library / DB)
- Skill nature
- TOOL
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 3
- Sub-category id
- 29
- Extractable
- True
- Also category
- False
Dimensions (API 2 worklist)
-
Relational Data Modeling Catalog dimension db id 216
Library dimension (catalog)
Roles linked in library: Fullstack Developer, PHP Backend Developer
-
Relational Database Design Catalog dimension db id 4
Library dimension (catalog)
Roles linked in library: .NET Backend Developer, Backend Developer, Kotlin Backend Developer, Node.js Backend Developer, Python Backend Developer, Ruby Backend Developer, Scala Backend Developer
-
Relational Database Usage Catalog dimension db id 371
Library dimension (catalog)
Roles linked in library: Go Backend Developer
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
Relational Data Modeling
relational-data-modeling
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Relational Database Design
relational-database-design
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Relational Database Usage
relational-database-usage
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
Aliases — catalog
- NoSQL (CANONICAL)
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Concept
- Sub-category
- Database Paradigm
- Confidence
- 0.93
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: NoSQL is broadly listed in job descriptions across backend/data roles, with MongoDB, DynamoDB, and Cassandra appearing as common market signals; it remains a hiring-pipeline staple rather than a niche or sunset tech.
Skill profile (library / DB)
- Skill nature
- CONCEPT
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 2
- Sub-category id
- 1019
- Extractable
- True
- Also category
- False
Dimensions (API 2 worklist)
-
NoSQL Databases Catalog dimension db id 19
Library dimension (catalog)
Roles linked in library: Backend Developer
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
NoSQL Databases
nosql-databases
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
Skill enrichment (orchestrator / LLM)
No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).
- Category
- Data Engineering Tools
- Sub-category
- general
- Skill nature
- PRACTICE
- Volatility
- MEDIUM
- Typical lifespan
- MULTI_YEAR
- Version strategy
- UNVERSIONED
Skill enrichment (orchestrator / LLM)
No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).
- Category
- Concepts
- Sub-category
- general
- Skill nature
- CONCEPT
- Volatility
- MEDIUM
- Typical lifespan
- MULTI_YEAR
- Version strategy
- UNVERSIONED
Aliases — catalog
- DevOps (CANONICAL)
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Methodology
- Sub-category
- Devops Methodology
- Confidence
- 0.97
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: DevOps appears in a large share of software and platform engineering job descriptions, often alongside CI/CD, Kubernetes, and cloud tooling; it is a standard hiring-pipeline keyword rather than a niche specialty.
Skill profile (library / DB)
- Skill nature
- METHODOLOGY
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 8
- Sub-category id
- 922
- Extractable
- True
- Also category
- False
Dimensions (API 2 worklist)
-
CI/CD Pipeline Platforms Catalog dimension db id 150
Library dimension (catalog)
Roles linked in library: DevOps Engineer
-
Deployment and Release Patterns Catalog dimension db id 140
Library dimension (catalog)
Roles linked in library: Cloud Architect
-
Infrastructure as Code Catalog dimension db id 132
Library dimension (catalog)
Roles linked in library: Cloud Architect, DevOps Engineer
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
CI/CD Pipeline Platforms
ci-cd-pipeline-platforms
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Deployment and Release Patterns
deployment-and-release-patterns
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Infrastructure as Code
infrastructure-as-code
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
All API 3 persistence rows
Same grid as the skill-extractor “Persistence items” table: one row per (skill × dimension) work item.
| Skill | Tag | Dimension | Skill↔dim | Role↔dim | Outcome | Notes |
|---|---|---|---|---|---|---|
| Google Cloud Platform | in_db |
Cloud & Hosting Providers
cloud-hosting-providers
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Google Cloud Platform | in_db |
Cloud Provider Platforms
cloud-provider-platforms
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Google Cloud Platform | in_db |
Cloud Security Posture Tools
cloud-security-posture-tools
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Python | in_db |
Cloud Security Scripting & DSL Languages
cloud-security-scripting-dsl-languages
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Python | in_db |
Programming Languages
programming-languages
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Python | in_db |
Programming Languages and Scripting
programming-languages-and-scripting
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Python | in_db |
Programming Languages for Data Work
programming-languages-for-data-work
|
✓ | ✓ | Existing dimension (library) · Role↔dimension saved | |
| Python | in_db |
Programming Languages for ML Systems
programming-languages-for-ml-systems
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Python | in_db |
Programming Languages for XR
programming-languages-for-xr
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Python | in_db |
Python Programming
python-programming
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Java | in_db |
Java Language and JVM
java-language-and-jvm
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Java | in_db |
Kotlin and Java
kotlin-and-java
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Java | in_db |
Native Mobile Languages
native-mobile-languages
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Java | in_db |
Pega Programming Languages & DSLs
pega-programming-languages-dsls
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Java | in_db |
Programming Languages
programming-languages
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Java | in_db |
Programming Languages for Data Work
programming-languages-for-data-work
|
✓ | ✓ | Existing dimension (library) · Role↔dimension saved | |
| PySpark | new |
ETL and ELT Tooling
etl-and-elt-tooling
|
— | — | Skipped — no persistable v3 meta for new skill | skill_not_in_db_v3_proposed |
| Spark | in_db |
ETL and ELT Tooling
etl-and-elt-tooling
|
✓ | ✓ | Existing dimension (library) · Role↔dimension saved | |
| Scala | in_db |
Programming Languages for Data Work
programming-languages-for-data-work
|
✓ | ✓ | Existing dimension (library) · Role↔dimension saved | |
| Scala | in_db |
Programming Languages for ML Systems
programming-languages-for-ml-systems
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Hadoop | in_db |
ETL and ELT Tooling
etl-and-elt-tooling
|
✓ | ✓ | Existing dimension (library) · Role↔dimension saved | |
| Bash | in_db |
Programming Languages and Scripting
programming-languages-and-scripting
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Bash | in_db |
Programming Languages for Data Work
programming-languages-for-data-work
|
✓ | ✓ | Existing dimension (library) · Role↔dimension saved | |
| Hive | in_db |
Local Persistence and Offline Behavior
local-persistence-and-offline-behavior
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Cassandra | in_db |
Cloud Storage and Data Services
cloud-storage-and-data-services
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| MySQL | in_db |
Relational Data Modeling
relational-data-modeling
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| MySQL | in_db |
Relational Database Design
relational-database-design
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| MySQL | in_db |
Relational Database Usage
relational-database-usage
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| NoSQL | in_db |
NoSQL Databases
nosql-databases
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| DevOps | in_db |
CI/CD Pipeline Platforms
ci-cd-pipeline-platforms
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| DevOps | in_db |
Deployment and Release Patterns
deployment-and-release-patterns
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| DevOps | in_db |
Infrastructure as Code
infrastructure-as-code
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
Library artifacts (this run)
| Kind | Detail | DB id |
|---|---|---|
| canonical_skill_proposed | HDFS | type=Data Engineering Tools subtype=general nature=TOOL lifespan=MULTI_YEAR | |
| canonical_skill_proposed | UNIX | type=Operating Systems subtype=general nature=PLATFORM lifespan=EVERGREEN | |
| canonical_skill_proposed | Pig | type=Data Engineering Tools subtype=general nature=TOOL lifespan=MULTI_YEAR | |
| canonical_skill_proposed | ETL | type=Data Engineering Tools subtype=general nature=PRACTICE lifespan=MULTI_YEAR | |
| canonical_skill_proposed | Data Science | type=Concepts subtype=general nature=CONCEPT lifespan=MULTI_YEAR | |
| dimension_skill_link_proposed | PySpark ↔ ETL and ELT Tooling | |
| role_dimension_link_proposed | Data Engineer ↔ ETL and ELT Tooling |
nano JD Parser — gpt-4.1-nano click to toggle
Show raw JSON
{
"JD_type": "pass",
"about_company": null,
"certifications": [],
"company_name": null,
"ctc": null,
"domain": {
"primary": {
"aliases": [],
"domain": "IT Services \u0026 Consulting"
},
"secondary": null
},
"education": [],
"experience": {
"max": null,
"min": 5,
"raw": "5+ years Data Engineering experience"
},
"job_locations": [],
"role": "Senior GCP Data Engineer",
"role_aliases": [
"GCP Data Engineer",
"Data Engineer",
"Cloud Data Engineer"
],
"role_archetype": "Data",
"roles_and_responsibilities": [
{
"bullet_count": 10,
"heading": "Responsibilities",
"heading_was_present": true,
"source_marker": {
"first_5_words": "\u25cf Designing and developing complex",
"last_5_words": "requirements dictated by the model/use case"
},
"text": "\u25cf Designing and developing complex and large-scale data structures and pipelines to organize, collect, and standardize data to generate insights and address reporting needs\n\u25cf Writing complex ETL (Extract / Transform / Load) processes, designs database systems and develops tools for real-time and offline analytic processing\n\u25cf Developing frameworks, standards \u0026 reference material for architecture and associated products\n\u25cf Designing data marts and data models to support Data Science and other internal customers.\n\u25cf Behaving as mentor to junior team members to provide technical advice\n\u25cf Applying knowledge of gcp-data tools and products to consult and advise on additional efforts across multiple domains spanning broader enterprise\n\u25cf Collaborating with data science team to transform data and integrate algorithms and models into highly available, production systems\n\u25cf Using in-depth knowledge on Hadoop architecture and HDFS commands and experience designing \u0026 optimizing queries to build scalable, modular, and efficient data pipelines\n\u25cf Using advanced programming skills in Python, Java, PySpark, or any of the major languages to build robust data pipelines and dynamic systems\n\u25cf Integrating data from a variety of sources, assuring that they adhere to data quality and accessibility standards\n\u25cf Experimenting with available tools and advice on new tools in order to determine optimal solution given the requirements dictated by the model/use case",
"word_count": 211
},
{
"bullet_count": 10,
"heading": "Requirements",
"heading_was_present": true,
"source_marker": {
"first_5_words": "\u25cf 5+ years Data Engineering experience",
"last_5_words": "constantly demands you to learn."
},
"text": "\u25cf 5+ years Data Engineering experience\n\u25cf 5+ years PySpark (Spark/Scala)\n\u25cf 3+ years advanced knowledge in Hadoop architecture, HDFS commands and experience designing \u0026 optimising queries against data in the HDFS environment\n\u25cf 2+ years\u0027 experience with Google Cloud Platform ( GCP )\n\u25cf Experience with bash shell scripts, UNIX utilities \u0026 UNIX Commands\n\u25cf Experience building and implementing data transformation and processing solutions\n\u25cf Advanced knowledge in Java, Python, Hive, Cassandra, Pig, MySQL or NoSQL or similar\n\u25cf If you are passionate about DevOps and GCP, and if you thrive in a collaborative and fast-paced environment\n\u25cf You like to solve puzzles and figure things out, how they work, how they operate etc.\n\u25cf You thrive in an environment that constantly demands you to learn.",
"word_count": 134
}
],
"urls": []
}
API 1 — extract-from-jd click to toggle
{
"final_skills": [
{
"is_primary": true,
"skill_name": "Google Cloud Platform"
},
{
"is_primary": true,
"skill_name": "Python"
},
{
"is_primary": true,
"skill_name": "Java"
},
{
"is_primary": true,
"skill_name": "PySpark"
},
{
"is_primary": true,
"skill_name": "Spark"
},
{
"is_primary": false,
"skill_name": "Scala"
},
{
"is_primary": true,
"skill_name": "Hadoop"
},
{
"is_primary": true,
"skill_name": "HDFS"
},
{
"is_primary": false,
"skill_name": "Bash"
},
{
"is_primary": false,
"skill_name": "UNIX"
},
{
"is_primary": false,
"skill_name": "Hive"
},
{
"is_primary": false,
"skill_name": "Cassandra"
},
{
"is_primary": false,
"skill_name": "Pig"
},
{
"is_primary": false,
"skill_name": "MySQL"
},
{
"is_primary": false,
"skill_name": "NoSQL"
},
{
"is_primary": true,
"skill_name": "ETL"
},
{
"is_primary": false,
"skill_name": "Data Science"
},
{
"is_primary": false,
"skill_name": "DevOps"
}
],
"jd_role": {
"display_name": "Senior GCP Data Engineer",
"rationale": null,
"role_aliases": [
"GCP Data Engineer",
"Data Engineer",
"Cloud Data Engineer"
],
"role_archetype": "Data",
"slug": ""
},
"nano_parsed": {
"JD_type": "pass",
"about_company": null,
"certifications": [],
"company_name": null,
"ctc": null,
"domain": {
"primary": {
"aliases": [],
"domain": "IT Services \u0026 Consulting"
},
"secondary": null
},
"education": [],
"experience": {
"max": null,
"min": 5,
"raw": "5+ years Data Engineering experience"
},
"job_locations": [],
"role": "Senior GCP Data Engineer",
"role_aliases": [
"GCP Data Engineer",
"Data Engineer",
"Cloud Data Engineer"
],
"role_archetype": "Data",
"roles_and_responsibilities": [
{
"bullet_count": 10,
"heading": "Responsibilities",
"heading_was_present": true,
"source_marker": {
"first_5_words": "\u25cf Designing and developing complex",
"last_5_words": "requirements dictated by the model/use case"
},
"text": "\u25cf Designing and developing complex and large-scale data structures and pipelines to organize, collect, and standardize data to generate insights and address reporting needs\n\u25cf Writing complex ETL (Extract / Transform / Load) processes, designs database systems and develops tools for real-time and offline analytic processing\n\u25cf Developing frameworks, standards \u0026 reference material for architecture and associated products\n\u25cf Designing data marts and data models to support Data Science and other internal customers.\n\u25cf Behaving as mentor to junior team members to provide technical advice\n\u25cf Applying knowledge of gcp-data tools and products to consult and advise on additional efforts across multiple domains spanning broader enterprise\n\u25cf Collaborating with data science team to transform data and integrate algorithms and models into highly available, production systems\n\u25cf Using in-depth knowledge on Hadoop architecture and HDFS commands and experience designing \u0026 optimizing queries to build scalable, modular, and efficient data pipelines\n\u25cf Using advanced programming skills in Python, Java, PySpark, or any of the major languages to build robust data pipelines and dynamic systems\n\u25cf Integrating data from a variety of sources, assuring that they adhere to data quality and accessibility standards\n\u25cf Experimenting with available tools and advice on new tools in order to determine optimal solution given the requirements dictated by the model/use case",
"word_count": 211
},
{
"bullet_count": 10,
"heading": "Requirements",
"heading_was_present": true,
"source_marker": {
"first_5_words": "\u25cf 5+ years Data Engineering experience",
"last_5_words": "constantly demands you to learn."
},
"text": "\u25cf 5+ years Data Engineering experience\n\u25cf 5+ years PySpark (Spark/Scala)\n\u25cf 3+ years advanced knowledge in Hadoop architecture, HDFS commands and experience designing \u0026 optimising queries against data in the HDFS environment\n\u25cf 2+ years\u0027 experience with Google Cloud Platform ( GCP )\n\u25cf Experience with bash shell scripts, UNIX utilities \u0026 UNIX Commands\n\u25cf Experience building and implementing data transformation and processing solutions\n\u25cf Advanced knowledge in Java, Python, Hive, Cassandra, Pig, MySQL or NoSQL or similar\n\u25cf If you are passionate about DevOps and GCP, and if you thrive in a collaborative and fast-paced environment\n\u25cf You like to solve puzzles and figure things out, how they work, how they operate etc.\n\u25cf You thrive in an environment that constantly demands you to learn.",
"word_count": 134
}
],
"urls": []
},
"rejected": false,
"rejection_reason": null,
"run_id": "9eb27c7e-c22e-4e2c-8c17-6c24aff1efe1",
"stage3_signals": {
"alias_found": true,
"alias_match_roles": [
{
"display_name": "Data Engineer",
"kra_matches": null,
"matched_count": null,
"matched_skills": null,
"role_id": 2,
"score": 1.0,
"slug": "data-engineer",
"total_count": null
}
],
"kra_match_roles": [
{
"display_name": "Data Engineer",
"kra_matches": [
{
"kra_text": "Designs dimensional models, star schemas, data vault structures, and curated data mart tables to support BI tools and self-service analytics consumption.",
"sentence": "Designing data marts and data models to support Data Science and other internal customers.",
"similarity": 0.7409
},
{
"kra_text": "Builds data ingestion pipelines to collect data from transactional databases, third-party APIs, event streams, and file sources into centralized data platforms.",
"sentence": "Designing and developing complex and large-scale data structures and pipelines to organize, collect, and standardize data to generate insights and address reporting needs",
"similarity": 0.6349
},
{
"kra_text": "Develops batch and real-time streaming data pipelines using Apache Spark, Apache Kafka, Apache Flink, or Airflow for data movement and processing at scale.",
"sentence": "Using advanced programming skills in Python, Java, PySpark, or any of the major languages to build robust data pipelines and dynamic systems",
"similarity": 0.6342
}
],
"matched_count": null,
"matched_skills": null,
"role_id": 2,
"score": 0.67,
"slug": "data-engineer",
"total_count": null
},
{
"display_name": "Fullstack Developer",
"kra_matches": [
{
"kra_text": "Designs and queries relational databases like PostgreSQL and document stores like MongoDB, writing migrations, indexes, and optimized queries.",
"sentence": "Writing complex ETL (Extract / Transform / Load) processes, designs database systems and develops tools for real-time and offline analytic processing",
"similarity": 0.5344
},
{
"kra_text": "Designs and queries relational databases like PostgreSQL and document stores like MongoDB, writing migrations, indexes, and optimized queries.",
"sentence": "Using in-depth knowledge on Hadoop architecture and HDFS commands and experience designing \u0026 optimizing queries to build scalable, modular, and efficient data pipelines",
"similarity": 0.5226
},
{
"kra_text": "Designs and queries relational databases like PostgreSQL and document stores like MongoDB, writing migrations, indexes, and optimized queries.",
"sentence": "Designing and developing complex and large-scale data structures and pipelines to organize, collect, and standardize data to generate insights and address reporting needs",
"similarity": 0.5207
}
],
"matched_count": null,
"matched_skills": null,
"role_id": 15,
"score": 0.5259,
"slug": "full-stack-engineer",
"total_count": null
},
{
"display_name": "Svelte Frontend Developer",
"kra_matches": [
{
"kra_text": "backend data integration",
"sentence": "Integrating data from a variety of sources, assuring that they adhere to data quality and accessibility standards",
"similarity": 0.57
},
{
"kra_text": "backend data integration",
"sentence": "Experience building and implementing data transformation and processing solutions",
"similarity": 0.5071
},
{
"kra_text": "backend data integration",
"sentence": "Collaborating with data science team to transform data and integrate algorithms and models into highly available, production systems",
"similarity": 0.4715
}
],
"matched_count": null,
"matched_skills": null,
"role_id": 92,
"score": 0.5162,
"slug": "svelte-frontend-developer",
"total_count": null
},
{
"display_name": "Flutter Developer",
"kra_matches": [
{
"kra_text": "integrate external APIs and data sources",
"sentence": "Integrating data from a variety of sources, assuring that they adhere to data quality and accessibility standards",
"similarity": 0.5862
},
{
"kra_text": "collaborate with design, product, and backend teams",
"sentence": "Collaborating with data science team to transform data and integrate algorithms and models into highly available, production systems",
"similarity": 0.5108
},
{
"kra_text": "integrate external APIs and data sources",
"sentence": "Experience building and implementing data transformation and processing solutions",
"similarity": 0.4506
}
],
"matched_count": null,
"matched_skills": null,
"role_id": 74,
"score": 0.5159,
"slug": "flutter-developer",
"total_count": null
},
{
"display_name": "Java Backend Developer",
"kra_matches": [
{
"kra_text": "persistence and data modeling",
"sentence": "Designing data marts and data models to support Data Science and other internal customers.",
"similarity": 0.5318
},
{
"kra_text": "persistence and data modeling",
"sentence": "Experience building and implementing data transformation and processing solutions",
"similarity": 0.5019
},
{
"kra_text": "persistence and data modeling",
"sentence": "Designing and developing complex and large-scale data structures and pipelines to organize, collect, and standardize data to generate insights and address reporting needs",
"similarity": 0.4797
}
],
"matched_count": null,
"matched_skills": null,
"role_id": 79,
"score": 0.5045,
"slug": "java-backend-developer",
"total_count": null
}
],
"skill_match_roles": [
{
"display_name": "Data Engineer",
"kra_matches": null,
"matched_count": 4,
"matched_skills": [
"Apache Spark",
"Hadoop",
"Java",
"Python"
],
"role_id": 2,
"score": 0.5,
"slug": "data-engineer",
"total_count": 8
},
{
"display_name": "Fullstack Developer",
"kra_matches": null,
"matched_count": 2,
"matched_skills": [
"Java",
"Python"
],
"role_id": 15,
"score": 0.25,
"slug": "full-stack-engineer",
"total_count": 8
},
{
"display_name": "Backend Developer",
"kra_matches": null,
"matched_count": 2,
"matched_skills": [
"Java",
"Python"
],
"role_id": 1,
"score": 0.25,
"slug": "backend-engineer",
"total_count": 8
},
{
"display_name": "Cyber Security Engineer",
"kra_matches": null,
"matched_count": 2,
"matched_skills": [
"Google Cloud Platform",
"Python"
],
"role_id": 5,
"score": 0.25,
"slug": "cybersecurity-engineer",
"total_count": 8
},
{
"display_name": "Cloud Security Engineer",
"kra_matches": null,
"matched_count": 2,
"matched_skills": [
"Google Cloud Platform",
"Python"
],
"role_id": 23,
"score": 0.25,
"slug": "cloud-security-engineer",
"total_count": 8
}
]
},
"stage4_decision": {
"alias_collision_detected": false,
"case": "A",
"chosen_role": {
"display_name": "Data Engineer",
"kra_matches": null,
"matched_count": null,
"matched_skills": null,
"role_id": 2,
"score": 1.0,
"slug": "data-engineer",
"total_count": null
},
"confidence": 1.0,
"is_new_role": false,
"llm2_fired": false,
"llm2_reasoning": null,
"matched_dimensions": [],
"matched_kras": [],
"matched_skills": [],
"new_role_display_name": null,
"new_role_slug": null,
"queued": false,
"reasoning": "Exact alias hit on data-engineer (1.0) \u2014 no other alias at this confidence; skill_top data-engineer 0.50 does not contradict",
"sub_role": null
},
"stage5_updates": {
"centroid_n_after": 57,
"centroid_updated": true,
"collision_log_id": null,
"new_kra_attached": null,
"new_skills_attached": [
{
"is_primary": true,
"queue_id": 3829,
"role_display_name": "Data Engineer",
"role_slug": "data-engineer",
"skill_name": "PySpark",
"status": "pending"
},
{
"is_primary": true,
"queue_id": 3830,
"role_display_name": "Data Engineer",
"role_slug": "data-engineer",
"skill_name": "HDFS",
"status": "pending"
},
{
"is_primary": false,
"queue_id": 3831,
"role_display_name": "Data Engineer",
"role_slug": "data-engineer",
"skill_name": "UNIX",
"status": "pending"
},
{
"is_primary": false,
"queue_id": 3832,
"role_display_name": "Data Engineer",
"role_slug": "data-engineer",
"skill_name": "Pig",
"status": "pending"
},
{
"is_primary": true,
"queue_id": 3833,
"role_display_name": "Data Engineer",
"role_slug": "data-engineer",
"skill_name": "ETL",
"status": "pending"
},
{
"is_primary": false,
"queue_id": 3834,
"role_display_name": "Data Engineer",
"role_slug": "data-engineer",
"skill_name": "Data Science",
"status": "pending"
}
],
"queue_entry_id": null,
"v3_pipeline_triggered": false,
"v3_role_slug": null,
"v3_run_id": null
}
}
API 2 — extract-details
{
"alias_matches": [
{
"alias_persist_skipped_reason": "alias_text already exists for this canonical skill",
"alias_persisted": false,
"existing_alias_id": 741,
"existing_alias_text": "Google Cloud Platform",
"input_term": "Google Cloud Platform",
"matched_canonical": {
"category_id": 9,
"display_name": "Google Cloud Platform",
"id": 425,
"is_also_category": false,
"is_extractable": true,
"skill_nature": "PLATFORM",
"slug": "google-cloud-platform",
"sub_category_id": 46,
"typical_lifespan": "EVERGREEN",
"volatility": "STABLE"
},
"matched_via": "alias"
},
{
"alias_persist_skipped_reason": "alias_text already exists for this canonical skill",
"alias_persisted": false,
"existing_alias_id": 67,
"existing_alias_text": "Python",
"input_term": "Python",
"matched_canonical": {
"category_id": 6,
"display_name": "Python",
"id": 5,
"is_also_category": false,
"is_extractable": true,
"skill_nature": "LANGUAGE",
"slug": "python",
"sub_category_id": 96,
"typical_lifespan": "EVERGREEN",
"volatility": "STABLE"
},
"matched_via": "alias"
},
{
"alias_persist_skipped_reason": "alias_text already exists for this canonical skill",
"alias_persisted": false,
"existing_alias_id": 1,
"existing_alias_text": "Java",
"input_term": "Java",
"matched_canonical": {
"category_id": 6,
"display_name": "Java",
"id": 1,
"is_also_category": false,
"is_extractable": true,
"skill_nature": "LANGUAGE",
"slug": "java",
"sub_category_id": 96,
"typical_lifespan": "EVERGREEN",
"volatility": "STABLE"
},
"matched_via": "alias"
},
{
"alias_persist_skipped_reason": "TODO: REMOVE AFTER TESTING \u2014 alias DB write disabled",
"alias_persisted": false,
"existing_alias_id": 2004,
"existing_alias_text": "Apache Spark",
"input_term": "PySpark",
"matched_canonical": {
"category_id": 5,
"display_name": "Apache Spark",
"id": 1350,
"is_also_category": false,
"is_extractable": true,
"skill_nature": "FRAMEWORK",
"slug": "apache-spark",
"sub_category_id": 1021,
"typical_lifespan": "EVERGREEN",
"volatility": "STABLE"
},
"matched_via": "embedding_alias"
},
{
"alias_persist_skipped_reason": "alias_text already exists for this canonical skill",
"alias_persisted": false,
"existing_alias_id": 2510,
"existing_alias_text": "spark",
"input_term": "Spark",
"matched_canonical": {
"category_id": 5,
"display_name": "Apache Spark",
"id": 1350,
"is_also_category": false,
"is_extractable": true,
"skill_nature": "FRAMEWORK",
"slug": "apache-spark",
"sub_category_id": 1021,
"typical_lifespan": "EVERGREEN",
"volatility": "STABLE"
},
"matched_via": "alias"
},
{
"alias_persist_skipped_reason": "alias_text already exists for this canonical skill",
"alias_persisted": false,
"existing_alias_id": 272,
"existing_alias_text": "Scala",
"input_term": "Scala",
"matched_canonical": {
"category_id": 6,
"display_name": "Scala",
"id": 102,
"is_also_category": false,
"is_extractable": true,
"skill_nature": "LANGUAGE",
"slug": "scala",
"sub_category_id": 96,
"typical_lifespan": "EVERGREEN",
"volatility": "STABLE"
},
"matched_via": "alias"
},
{
"alias_persist_skipped_reason": "alias_text already exists for this canonical skill",
"alias_persisted": false,
"existing_alias_id": 2010,
"existing_alias_text": "Hadoop",
"input_term": "Hadoop",
"matched_canonical": {
"category_id": 5,
"display_name": "Hadoop",
"id": 1351,
"is_also_category": false,
"is_extractable": true,
"skill_nature": "FRAMEWORK",
"slug": "hadoop",
"sub_category_id": 91,
"typical_lifespan": "EVERGREEN",
"volatility": "STABLE"
},
"matched_via": "alias"
},
{
"alias_persist_skipped_reason": "alias_text already exists for this canonical skill",
"alias_persisted": false,
"existing_alias_id": 273,
"existing_alias_text": "Bash",
"input_term": "Bash",
"matched_canonical": {
"category_id": 6,
"display_name": "Bash",
"id": 103,
"is_also_category": false,
"is_extractable": true,
"skill_nature": "LANGUAGE",
"slug": "bash",
"sub_category_id": 238,
"typical_lifespan": "EVERGREEN",
"volatility": "STABLE"
},
"matched_via": "alias"
},
{
"alias_persist_skipped_reason": "alias_text already exists for this canonical skill",
"alias_persisted": false,
"existing_alias_id": 4198,
"existing_alias_text": "Hive",
"input_term": "Hive",
"matched_canonical": {
"category_id": 3,
"display_name": "Hive",
"id": 2754,
"is_also_category": false,
"is_extractable": true,
"skill_nature": "TOOL",
"slug": "hive",
"sub_category_id": 2242,
"typical_lifespan": "EVERGREEN",
"volatility": "STABLE"
},
"matched_via": "alias"
},
{
"alias_persist_skipped_reason": "alias_text already exists for this canonical skill",
"alias_persisted": false,
"existing_alias_id": 2013,
"existing_alias_text": "Cassandra",
"input_term": "Cassandra",
"matched_canonical": {
"category_id": 3,
"display_name": "Cassandra",
"id": 1354,
"is_also_category": false,
"is_extractable": true,
"skill_nature": "TOOL",
"slug": "cassandra",
"sub_category_id": 31,
"typical_lifespan": "EVERGREEN",
"volatility": "STABLE"
},
"matched_via": "alias"
},
{
"alias_persist_skipped_reason": "alias_text already exists for this canonical skill",
"alias_persisted": false,
"existing_alias_id": 134,
"existing_alias_text": "MySQL",
"input_term": "MySQL",
"matched_canonical": {
"category_id": 3,
"display_name": "MySQL",
"id": 17,
"is_also_category": false,
"is_extractable": true,
"skill_nature": "TOOL",
"slug": "mysql",
"sub_category_id": 29,
"typical_lifespan": "EVERGREEN",
"volatility": "STABLE"
},
"matched_via": "alias"
},
{
"alias_persist_skipped_reason": "alias_text already exists for this canonical skill",
"alias_persisted": false,
"existing_alias_id": 1989,
"existing_alias_text": "NoSQL",
"input_term": "NoSQL",
"matched_canonical": {
"category_id": 2,
"display_name": "NoSQL",
"id": 1346,
"is_also_category": false,
"is_extractable": true,
"skill_nature": "CONCEPT",
"slug": "nosql",
"sub_category_id": 1019,
"typical_lifespan": "EVERGREEN",
"volatility": "STABLE"
},
"matched_via": "alias"
},
{
"alias_persist_skipped_reason": "alias_text already exists for this canonical skill",
"alias_persisted": false,
"existing_alias_id": 1852,
"existing_alias_text": "DevOps",
"input_term": "DevOps",
"matched_canonical": {
"category_id": 8,
"display_name": "DevOps",
"id": 1216,
"is_also_category": false,
"is_extractable": true,
"skill_nature": "METHODOLOGY",
"slug": "devops",
"sub_category_id": 922,
"typical_lifespan": "EVERGREEN",
"volatility": "STABLE"
},
"matched_via": "alias"
}
],
"candidate_roles": [
{
"display_name": "PHP Backend Developer",
"id": 86,
"rationale": null,
"role_archetype": "Engineering",
"slug": "php-backend-developer",
"source": "db"
},
{
"display_name": "Cloud Architect",
"id": 9,
"rationale": null,
"role_archetype": null,
"slug": "cloud-architect",
"source": "db"
},
{
"display_name": "Cloud Security Engineer",
"id": 23,
"rationale": null,
"role_archetype": null,
"slug": "cloud-security-engineer",
"source": "db"
},
{
"display_name": "Cyber Security Engineer",
"id": 5,
"rationale": null,
"role_archetype": null,
"slug": "cybersecurity-engineer",
"source": "db"
},
{
"display_name": "Backend Developer",
"id": 1,
"rationale": null,
"role_archetype": "A Backend Engineer designs, builds, and maintains the server-side logic and data handling that power applications and services. They focus on implementing reliable business functionality, integrating with other systems, and ensuring the backend is scalable, maintainable, and observable.",
"slug": "backend-engineer",
"source": "db"
},
{
"display_name": "Fullstack Developer",
"id": 15,
"rationale": null,
"role_archetype": null,
"slug": "full-stack-engineer",
"source": "db"
},
{
"display_name": "Data Engineer",
"id": 2,
"rationale": null,
"role_archetype": null,
"slug": "data-engineer",
"source": "db"
},
{
"display_name": "ML Engineer",
"id": 3,
"rationale": null,
"role_archetype": null,
"slug": "ml-engineer",
"source": "db"
},
{
"display_name": "MLOps Engineer",
"id": 16,
"rationale": null,
"role_archetype": null,
"slug": "ml-ops-engineer",
"source": "db"
},
{
"display_name": "AR/VR Engineer",
"id": 8,
"rationale": null,
"role_archetype": null,
"slug": "ar-vr-engineer",
"source": "db"
},
{
"display_name": "Python Backend Developer",
"id": 80,
"rationale": null,
"role_archetype": "Engineering",
"slug": "python-backend-developer",
"source": "db"
},
{
"display_name": "Java Backend Developer",
"id": 79,
"rationale": null,
"role_archetype": "Engineering",
"slug": "java-backend-developer",
"source": "db"
},
{
"display_name": "Kotlin Backend Developer",
"id": 84,
"rationale": null,
"role_archetype": "Engineering",
"slug": "kotlin-server-backend-developer",
"source": "db"
},
{
"display_name": "Scala Backend Developer",
"id": 87,
"rationale": null,
"role_archetype": "Engineering",
"slug": "scala-backend-developer",
"source": "db"
},
{
"display_name": "Android Developer",
"id": 4,
"rationale": null,
"role_archetype": null,
"slug": "android-engineer",
"source": "db"
},
{
"display_name": "Native Mobile Developer",
"id": 75,
"rationale": null,
"role_archetype": "Engineering",
"slug": "native-mobile-developer",
"source": "db"
},
{
"display_name": "Pega Developer",
"id": 24,
"rationale": null,
"role_archetype": null,
"slug": "pega-developer",
"source": "db"
},
{
"display_name": "Flutter Developer",
"id": 74,
"rationale": null,
"role_archetype": "Engineering",
"slug": "flutter-developer",
"source": "db"
},
{
"display_name": "Hybrid Mobile Developer",
"id": 11,
"rationale": null,
"role_archetype": null,
"slug": "hybrid-mobile-developer",
"source": "db"
},
{
"display_name": "React Native Developer",
"id": 73,
"rationale": null,
"role_archetype": "Engineering",
"slug": "react-native-developer",
"source": "db"
},
{
"display_name": "iOS Developer",
"id": 6,
"rationale": null,
"role_archetype": null,
"slug": "ios-engineer",
"source": "db"
},
{
"display_name": ".NET Backend Developer",
"id": 83,
"rationale": null,
"role_archetype": "Engineering",
"slug": "dotnet-backend-developer",
"source": "db"
},
{
"display_name": "Node.js Backend Developer",
"id": 82,
"rationale": null,
"role_archetype": "Engineering",
"slug": "node-backend-developer",
"source": "db"
},
{
"display_name": "Ruby Backend Developer",
"id": 85,
"rationale": null,
"role_archetype": "Engineering",
"slug": "ruby-backend-developer",
"source": "db"
},
{
"display_name": "Go Backend Developer",
"id": 81,
"rationale": null,
"role_archetype": "Engineering",
"slug": "go-backend-developer",
"source": "db"
},
{
"display_name": "DevOps Engineer",
"id": 10,
"rationale": null,
"role_archetype": null,
"slug": "devops-engineer",
"source": "db"
}
],
"chosen_role": {
"display_name": "Data Engineer",
"id": 2,
"rationale": "Exact alias hit on data-engineer (1.0) \u2014 no other alias at this confidence; skill_top data-engineer 0.50 does not contradict",
"role_archetype": null,
"slug": "data-engineer",
"source": "db"
},
"dimensions": [
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Cloud \u0026 Hosting Providers",
"id": 414,
"rationale": "Knowledge of major cloud and hosting vendor platforms for deploying and managing PHP applications.",
"slug": "cloud-hosting-providers",
"source": "db"
},
"input_skill": "Google Cloud Platform",
"llm_role": null,
"roles_from_db": [
{
"display_name": "PHP Backend Developer",
"id": 86,
"rationale": null,
"role_archetype": "Engineering",
"slug": "php-backend-developer",
"source": "db"
}
]
},
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Cloud Provider Platforms",
"id": 131,
"rationale": "Major cloud platforms and their core service ecosystems used to design target-state architectures, choose deployment boundaries, and evaluate managed capabilities. This is the primary substrate for cloud architecture decisions.",
"slug": "cloud-provider-platforms",
"source": "db"
},
"input_skill": "Google Cloud Platform",
"llm_role": null,
"roles_from_db": [
{
"display_name": "Cloud Architect",
"id": 9,
"rationale": null,
"role_archetype": null,
"slug": "cloud-architect",
"source": "db"
},
{
"display_name": "Cloud Security Engineer",
"id": 23,
"rationale": null,
"role_archetype": null,
"slug": "cloud-security-engineer",
"source": "db"
}
]
},
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Cloud Security Posture Tools",
"id": 64,
"rationale": "Cloud-native security platforms used to assess misconfiguration, workload exposure, and cloud control coverage. This dimension includes the major CNAPP/CSPM/CWPP vendors and cloud security services the role reviews and tunes.",
"slug": "cloud-security-posture-tools",
"source": "db"
},
"input_skill": "Google Cloud Platform",
"llm_role": null,
"roles_from_db": [
{
"display_name": "Cloud Security Engineer",
"id": 23,
"rationale": null,
"role_archetype": null,
"slug": "cloud-security-engineer",
"source": "db"
},
{
"display_name": "Cyber Security Engineer",
"id": 5,
"rationale": null,
"role_archetype": null,
"slug": "cybersecurity-engineer",
"source": "db"
}
]
},
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Cloud Security Scripting \u0026 DSL Languages",
"id": 248,
"rationale": "Proficiency in programming and domain-specific languages used to automate and script cloud security controls.",
"slug": "cloud-security-scripting-dsl-languages",
"source": "db"
},
"input_skill": "Python",
"llm_role": null,
"roles_from_db": [
{
"display_name": "Cloud Security Engineer",
"id": 23,
"rationale": null,
"role_archetype": null,
"slug": "cloud-security-engineer",
"source": "db"
}
]
},
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Programming Languages",
"id": 1,
"rationale": "Primary implementation languages used to build client and server feature code. Full stack engineers need enough fluency to move across layers and implement product behavior end to end.",
"slug": "programming-languages",
"source": "db"
},
"input_skill": "Python",
"llm_role": null,
"roles_from_db": [
{
"display_name": "Backend Developer",
"id": 1,
"rationale": null,
"role_archetype": "A Backend Engineer designs, builds, and maintains the server-side logic and data handling that power applications and services. They focus on implementing reliable business functionality, integrating with other systems, and ensuring the backend is scalable, maintainable, and observable.",
"slug": "backend-engineer",
"source": "db"
},
{
"display_name": "Fullstack Developer",
"id": 15,
"rationale": null,
"role_archetype": null,
"slug": "full-stack-engineer",
"source": "db"
}
]
},
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Programming Languages and Scripting",
"id": 59,
"rationale": "Languages used to write security automation, analysis scripts, detection logic, and remediation helpers. This is the primary implementation surface for a cybersecurity engineer across tooling and response workflows.",
"slug": "programming-languages-and-scripting",
"source": "db"
},
"input_skill": "Python",
"llm_role": null,
"roles_from_db": [
{
"display_name": "Cyber Security Engineer",
"id": 5,
"rationale": null,
"role_archetype": null,
"slug": "cybersecurity-engineer",
"source": "db"
}
]
},
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Programming Languages for Data Work",
"id": 21,
"rationale": "Languages used to implement data pipelines, transformations, and operational glue. This is the primary coding surface for building ingestion, enrichment, and automation logic in data engineering.",
"slug": "programming-languages-for-data-work",
"source": "db"
},
"input_skill": "Python",
"llm_role": null,
"roles_from_db": [
{
"display_name": "Data Engineer",
"id": 2,
"rationale": null,
"role_archetype": null,
"slug": "data-engineer",
"source": "db"
}
]
},
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Programming Languages for ML Systems",
"id": 39,
"rationale": "Languages used to build training code, inference services, evaluation jobs, and ML glue code. This is the primary implementation surface for ML engineers across experimentation and productionization.",
"slug": "programming-languages-for-ml-systems",
"source": "db"
},
"input_skill": "Python",
"llm_role": null,
"roles_from_db": [
{
"display_name": "ML Engineer",
"id": 3,
"rationale": null,
"role_archetype": null,
"slug": "ml-engineer",
"source": "db"
},
{
"display_name": "MLOps Engineer",
"id": 16,
"rationale": null,
"role_archetype": null,
"slug": "ml-ops-engineer",
"source": "db"
}
]
},
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Programming Languages for XR",
"id": 97,
"rationale": "Primary implementation languages used to build immersive client features, interaction logic, and device-specific runtime behavior. This is the core coding surface for AR/VR experiences.",
"slug": "programming-languages-for-xr",
"source": "db"
},
"input_skill": "Python",
"llm_role": null,
"roles_from_db": [
{
"display_name": "AR/VR Engineer",
"id": 8,
"rationale": null,
"role_archetype": null,
"slug": "ar-vr-engineer",
"source": "db"
}
]
},
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Python Programming",
"id": 290,
"rationale": "Core Python language skills used to implement backend business logic, request handlers, integrations, and service internals. This is the primary coding surface for the role.",
"slug": "python-programming",
"source": "db"
},
"input_skill": "Python",
"llm_role": null,
"roles_from_db": [
{
"display_name": "Python Backend Developer",
"id": 80,
"rationale": null,
"role_archetype": "Engineering",
"slug": "python-backend-developer",
"source": "db"
}
]
},
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Java Language and JVM",
"id": 279,
"rationale": "Core Java implementation skills used to build backend service logic, utilities, and internal abstractions. This is the primary coding surface for the role and includes language features plus JVM behavior that affect correctness and maintainability.",
"slug": "java-language-and-jvm",
"source": "db"
},
"input_skill": "Java",
"llm_role": null,
"roles_from_db": [
{
"display_name": "Java Backend Developer",
"id": 79,
"rationale": null,
"role_archetype": "Engineering",
"slug": "java-backend-developer",
"source": "db"
},
{
"display_name": "Kotlin Backend Developer",
"id": 84,
"rationale": null,
"role_archetype": "Engineering",
"slug": "kotlin-server-backend-developer",
"source": "db"
},
{
"display_name": "Scala Backend Developer",
"id": 87,
"rationale": null,
"role_archetype": "Engineering",
"slug": "scala-backend-developer",
"source": "db"
}
]
},
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Kotlin and Java",
"id": 161,
"rationale": "Primary implementation languages for Android app features, platform integration, and client-side business logic. Android engineers use these languages to build screens, state flows, service adapters, and device-aware behavior.",
"slug": "kotlin-and-java",
"source": "db"
},
"input_skill": "Java",
"llm_role": null,
"roles_from_db": [
{
"display_name": "Android Developer",
"id": 4,
"rationale": null,
"role_archetype": null,
"slug": "android-engineer",
"source": "db"
}
]
},
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Native Mobile Languages",
"id": 274,
"rationale": "Primary implementation languages used to build platform-specific app features, UI logic, and device integrations. This is the core coding surface for native mobile work on one platform.",
"slug": "native-mobile-languages",
"source": "db"
},
"input_skill": "Java",
"llm_role": null,
"roles_from_db": [
{
"display_name": "Native Mobile Developer",
"id": 75,
"rationale": null,
"role_archetype": "Engineering",
"slug": "native-mobile-developer",
"source": "db"
}
]
},
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Pega Programming Languages \u0026 DSLs",
"id": 267,
"rationale": "Programming languages and domain-specific languages used in Pega development.",
"slug": "pega-programming-languages-dsls",
"source": "db"
},
"input_skill": "Java",
"llm_role": null,
"roles_from_db": [
{
"display_name": "Pega Developer",
"id": 24,
"rationale": null,
"role_archetype": null,
"slug": "pega-developer",
"source": "db"
}
]
},
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Programming Languages",
"id": 1,
"rationale": "Primary implementation languages used to build client and server feature code. Full stack engineers need enough fluency to move across layers and implement product behavior end to end.",
"slug": "programming-languages",
"source": "db"
},
"input_skill": "Java",
"llm_role": null,
"roles_from_db": [
{
"display_name": "Backend Developer",
"id": 1,
"rationale": null,
"role_archetype": "A Backend Engineer designs, builds, and maintains the server-side logic and data handling that power applications and services. They focus on implementing reliable business functionality, integrating with other systems, and ensuring the backend is scalable, maintainable, and observable.",
"slug": "backend-engineer",
"source": "db"
},
{
"display_name": "Fullstack Developer",
"id": 15,
"rationale": null,
"role_archetype": null,
"slug": "full-stack-engineer",
"source": "db"
}
]
},
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Programming Languages for Data Work",
"id": 21,
"rationale": "Languages used to implement data pipelines, transformations, and operational glue. This is the primary coding surface for building ingestion, enrichment, and automation logic in data engineering.",
"slug": "programming-languages-for-data-work",
"source": "db"
},
"input_skill": "Java",
"llm_role": null,
"roles_from_db": [
{
"display_name": "Data Engineer",
"id": 2,
"rationale": null,
"role_archetype": null,
"slug": "data-engineer",
"source": "db"
}
]
},
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "ETL and ELT Tooling",
"id": 24,
"rationale": "Packaged tools for extracting, loading, and transforming data across systems. This dimension covers connector-based ingestion, transformation frameworks, and managed integration products.",
"slug": "etl-and-elt-tooling",
"source": "db"
},
"input_skill": "PySpark",
"llm_role": null,
"roles_from_db": [
{
"display_name": "Data Engineer",
"id": 2,
"rationale": null,
"role_archetype": null,
"slug": "data-engineer",
"source": "db"
}
]
},
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "ETL and ELT Tooling",
"id": 24,
"rationale": "Packaged tools for extracting, loading, and transforming data across systems. This dimension covers connector-based ingestion, transformation frameworks, and managed integration products.",
"slug": "etl-and-elt-tooling",
"source": "db"
},
"input_skill": "Spark",
"llm_role": null,
"roles_from_db": [
{
"display_name": "Data Engineer",
"id": 2,
"rationale": null,
"role_archetype": null,
"slug": "data-engineer",
"source": "db"
}
]
},
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Programming Languages for Data Work",
"id": 21,
"rationale": "Languages used to implement data pipelines, transformations, and operational glue. This is the primary coding surface for building ingestion, enrichment, and automation logic in data engineering.",
"slug": "programming-languages-for-data-work",
"source": "db"
},
"input_skill": "Scala",
"llm_role": null,
"roles_from_db": [
{
"display_name": "Data Engineer",
"id": 2,
"rationale": null,
"role_archetype": null,
"slug": "data-engineer",
"source": "db"
}
]
},
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Programming Languages for ML Systems",
"id": 39,
"rationale": "Languages used to build training code, inference services, evaluation jobs, and ML glue code. This is the primary implementation surface for ML engineers across experimentation and productionization.",
"slug": "programming-languages-for-ml-systems",
"source": "db"
},
"input_skill": "Scala",
"llm_role": null,
"roles_from_db": [
{
"display_name": "ML Engineer",
"id": 3,
"rationale": null,
"role_archetype": null,
"slug": "ml-engineer",
"source": "db"
},
{
"display_name": "MLOps Engineer",
"id": 16,
"rationale": null,
"role_archetype": null,
"slug": "ml-ops-engineer",
"source": "db"
}
]
},
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "ETL and ELT Tooling",
"id": 24,
"rationale": "Packaged tools for extracting, loading, and transforming data across systems. This dimension covers connector-based ingestion, transformation frameworks, and managed integration products.",
"slug": "etl-and-elt-tooling",
"source": "db"
},
"input_skill": "Hadoop",
"llm_role": null,
"roles_from_db": [
{
"display_name": "Data Engineer",
"id": 2,
"rationale": null,
"role_archetype": null,
"slug": "data-engineer",
"source": "db"
}
]
},
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Programming Languages and Scripting",
"id": 59,
"rationale": "Languages used to write security automation, analysis scripts, detection logic, and remediation helpers. This is the primary implementation surface for a cybersecurity engineer across tooling and response workflows.",
"slug": "programming-languages-and-scripting",
"source": "db"
},
"input_skill": "Bash",
"llm_role": null,
"roles_from_db": [
{
"display_name": "Cyber Security Engineer",
"id": 5,
"rationale": null,
"role_archetype": null,
"slug": "cybersecurity-engineer",
"source": "db"
}
]
},
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Programming Languages for Data Work",
"id": 21,
"rationale": "Languages used to implement data pipelines, transformations, and operational glue. This is the primary coding surface for building ingestion, enrichment, and automation logic in data engineering.",
"slug": "programming-languages-for-data-work",
"source": "db"
},
"input_skill": "Bash",
"llm_role": null,
"roles_from_db": [
{
"display_name": "Data Engineer",
"id": 2,
"rationale": null,
"role_archetype": null,
"slug": "data-engineer",
"source": "db"
}
]
},
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Local Persistence and Offline Behavior",
"id": 85,
"rationale": "On-device storage used for caching, offline support, and durable client state. This cluster is coherent because iOS apps often need to preserve user progress and data when connectivity is limited.",
"slug": "local-persistence-and-offline-behavior",
"source": "db"
},
"input_skill": "Hive",
"llm_role": null,
"roles_from_db": [
{
"display_name": "Android Developer",
"id": 4,
"rationale": null,
"role_archetype": null,
"slug": "android-engineer",
"source": "db"
},
{
"display_name": "Flutter Developer",
"id": 74,
"rationale": null,
"role_archetype": "Engineering",
"slug": "flutter-developer",
"source": "db"
},
{
"display_name": "Hybrid Mobile Developer",
"id": 11,
"rationale": null,
"role_archetype": null,
"slug": "hybrid-mobile-developer",
"source": "db"
},
{
"display_name": "Native Mobile Developer",
"id": 75,
"rationale": null,
"role_archetype": "Engineering",
"slug": "native-mobile-developer",
"source": "db"
},
{
"display_name": "React Native Developer",
"id": 73,
"rationale": null,
"role_archetype": "Engineering",
"slug": "react-native-developer",
"source": "db"
},
{
"display_name": "iOS Developer",
"id": 6,
"rationale": null,
"role_archetype": null,
"slug": "ios-engineer",
"source": "db"
}
]
},
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Cloud Storage and Data Services",
"id": 144,
"rationale": "Cloud-native storage and managed data services used to place workloads, choose durability tiers, and define platform boundaries. This is a coherent cluster because architects evaluate storage fit, access patterns, and managed service tradeoffs.",
"slug": "cloud-storage-and-data-services",
"source": "db"
},
"input_skill": "Cassandra",
"llm_role": null,
"roles_from_db": [
{
"display_name": "Cloud Architect",
"id": 9,
"rationale": null,
"role_archetype": null,
"slug": "cloud-architect",
"source": "db"
}
]
},
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Relational Data Modeling",
"id": 216,
"rationale": "Modeling and tuning relational persistence for backend features. PHP backend developers need this to shape schemas, indexes, transactions, and query-aware data structures that support application behavior.",
"slug": "relational-data-modeling",
"source": "db"
},
"input_skill": "MySQL",
"llm_role": null,
"roles_from_db": [
{
"display_name": "Fullstack Developer",
"id": 15,
"rationale": null,
"role_archetype": null,
"slug": "full-stack-engineer",
"source": "db"
},
{
"display_name": "PHP Backend Developer",
"id": 86,
"rationale": null,
"role_archetype": "Engineering",
"slug": "php-backend-developer",
"source": "db"
}
]
},
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Relational Database Design",
"id": 4,
"rationale": "Modeling and operating relational persistence for backend services. Includes schema design, normalization, indexing, transactions, and query tuning for operational data stores.",
"slug": "relational-database-design",
"source": "db"
},
"input_skill": "MySQL",
"llm_role": null,
"roles_from_db": [
{
"display_name": ".NET Backend Developer",
"id": 83,
"rationale": null,
"role_archetype": "Engineering",
"slug": "dotnet-backend-developer",
"source": "db"
},
{
"display_name": "Backend Developer",
"id": 1,
"rationale": null,
"role_archetype": "A Backend Engineer designs, builds, and maintains the server-side logic and data handling that power applications and services. They focus on implementing reliable business functionality, integrating with other systems, and ensuring the backend is scalable, maintainable, and observable.",
"slug": "backend-engineer",
"source": "db"
},
{
"display_name": "Kotlin Backend Developer",
"id": 84,
"rationale": null,
"role_archetype": "Engineering",
"slug": "kotlin-server-backend-developer",
"source": "db"
},
{
"display_name": "Node.js Backend Developer",
"id": 82,
"rationale": null,
"role_archetype": "Engineering",
"slug": "node-backend-developer",
"source": "db"
},
{
"display_name": "Python Backend Developer",
"id": 80,
"rationale": null,
"role_archetype": "Engineering",
"slug": "python-backend-developer",
"source": "db"
},
{
"display_name": "Ruby Backend Developer",
"id": 85,
"rationale": null,
"role_archetype": "Engineering",
"slug": "ruby-backend-developer",
"source": "db"
},
{
"display_name": "Scala Backend Developer",
"id": 87,
"rationale": null,
"role_archetype": "Engineering",
"slug": "scala-backend-developer",
"source": "db"
}
]
},
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Relational Database Usage",
"id": 371,
"rationale": "Working effectively with operational relational databases from Go backend services. This includes schema-aware querying, indexing awareness, transactions, and understanding how service code interacts with PostgreSQL or similar systems.",
"slug": "relational-database-usage",
"source": "db"
},
"input_skill": "MySQL",
"llm_role": null,
"roles_from_db": [
{
"display_name": "Go Backend Developer",
"id": 81,
"rationale": null,
"role_archetype": "Engineering",
"slug": "go-backend-developer",
"source": "db"
}
]
},
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "NoSQL Databases",
"id": 19,
"rationale": "Models and manages data using non-relational database systems.",
"slug": "nosql-databases",
"source": "db"
},
"input_skill": "NoSQL",
"llm_role": null,
"roles_from_db": [
{
"display_name": "Backend Developer",
"id": 1,
"rationale": null,
"role_archetype": "A Backend Engineer designs, builds, and maintains the server-side logic and data handling that power applications and services. They focus on implementing reliable business functionality, integrating with other systems, and ensuring the backend is scalable, maintainable, and observable.",
"slug": "backend-engineer",
"source": "db"
}
]
},
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "CI/CD Pipeline Platforms",
"id": 150,
"rationale": "Systems used to define, run, and maintain automated build and deployment workflows. This cluster is coherent because the role owns delivery automation end to end, including pipeline reliability and promotion logic.",
"slug": "ci-cd-pipeline-platforms",
"source": "db"
},
"input_skill": "DevOps",
"llm_role": null,
"roles_from_db": [
{
"display_name": "DevOps Engineer",
"id": 10,
"rationale": null,
"role_archetype": null,
"slug": "devops-engineer",
"source": "db"
}
]
},
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Deployment and Release Patterns",
"id": 140,
"rationale": "Patterns for promoting changes safely across environments, including rollout, rollback, and release gating strategies. Cloud Architects define these patterns so teams can deploy consistently across the platform.",
"slug": "deployment-and-release-patterns",
"source": "db"
},
"input_skill": "DevOps",
"llm_role": null,
"roles_from_db": [
{
"display_name": "Cloud Architect",
"id": 9,
"rationale": null,
"role_archetype": null,
"slug": "cloud-architect",
"source": "db"
}
]
},
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Infrastructure as Code",
"id": 132,
"rationale": "Declarative provisioning and environment definition tools used to codify cloud infrastructure, repeatable environments, and platform standards. Cloud Architects use these to express reference architectures and guardrails.",
"slug": "infrastructure-as-code",
"source": "db"
},
"input_skill": "DevOps",
"llm_role": null,
"roles_from_db": [
{
"display_name": "Cloud Architect",
"id": 9,
"rationale": null,
"role_archetype": null,
"slug": "cloud-architect",
"source": "db"
},
{
"display_name": "DevOps Engineer",
"id": 10,
"rationale": null,
"role_archetype": null,
"slug": "devops-engineer",
"source": "db"
}
]
}
],
"input_final_skills": [
"Google Cloud Platform",
"Python",
"Java",
"PySpark",
"Spark",
"Scala",
"Hadoop",
"HDFS",
"Bash",
"UNIX",
"Hive",
"Cassandra",
"Pig",
"MySQL",
"NoSQL",
"ETL",
"Data Science",
"DevOps"
],
"input_llm_skills": [
"Google Cloud Platform",
"Python",
"Java",
"PySpark",
"Spark",
"Scala",
"Hadoop",
"HDFS",
"Bash",
"UNIX",
"Hive",
"Cassandra",
"Pig",
"MySQL",
"NoSQL",
"ETL",
"Data Science",
"DevOps"
],
"new_aliases_persisted": 0,
"run_id": "9eb27c7e-c22e-4e2c-8c17-6c24aff1efe1",
"skills_detail": [
{
"aliases_in_db": [
{
"alias_text": "Google Cloud Platform",
"alias_type": "CANONICAL",
"id": 741,
"is_primary": true,
"match_strategy": "CASE_INSENSITIVE"
}
],
"canonical": {
"category_id": 9,
"display_name": "Google Cloud Platform",
"id": 425,
"is_also_category": false,
"is_extractable": true,
"skill_nature": "PLATFORM",
"slug": "google-cloud-platform",
"sub_category_id": 46,
"typical_lifespan": "EVERGREEN",
"volatility": "STABLE"
},
"dimensions": [
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Cloud \u0026 Hosting Providers",
"id": 414,
"rationale": "Knowledge of major cloud and hosting vendor platforms for deploying and managing PHP applications.",
"slug": "cloud-hosting-providers",
"source": "db"
},
"input_skill": "Google Cloud Platform",
"llm_role": null,
"roles_from_db": [
{
"display_name": "PHP Backend Developer",
"id": 86,
"rationale": null,
"role_archetype": "Engineering",
"slug": "php-backend-developer",
"source": "db"
}
]
},
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Cloud Provider Platforms",
"id": 131,
"rationale": "Major cloud platforms and their core service ecosystems used to design target-state architectures, choose deployment boundaries, and evaluate managed capabilities. This is the primary substrate for cloud architecture decisions.",
"slug": "cloud-provider-platforms",
"source": "db"
},
"input_skill": "Google Cloud Platform",
"llm_role": null,
"roles_from_db": [
{
"display_name": "Cloud Architect",
"id": 9,
"rationale": null,
"role_archetype": null,
"slug": "cloud-architect",
"source": "db"
},
{
"display_name": "Cloud Security Engineer",
"id": 23,
"rationale": null,
"role_archetype": null,
"slug": "cloud-security-engineer",
"source": "db"
}
]
},
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Cloud Security Posture Tools",
"id": 64,
"rationale": "Cloud-native security platforms used to assess misconfiguration, workload exposure, and cloud control coverage. This dimension includes the major CNAPP/CSPM/CWPP vendors and cloud security services the role reviews and tunes.",
"slug": "cloud-security-posture-tools",
"source": "db"
},
"input_skill": "Google Cloud Platform",
"llm_role": null,
"roles_from_db": [
{
"display_name": "Cloud Security Engineer",
"id": 23,
"rationale": null,
"role_archetype": null,
"slug": "cloud-security-engineer",
"source": "db"
},
{
"display_name": "Cyber Security Engineer",
"id": 5,
"rationale": null,
"role_archetype": null,
"slug": "cybersecurity-engineer",
"source": "db"
}
]
}
],
"input_skill": "Google Cloud Platform",
"matched_via": "alias",
"new_alias_persisted": false,
"new_alias_text": null,
"new_skill_meta": null,
"source_tag": "db",
"was_in_llm_skills": true
},
{
"aliases_in_db": [
{
"alias_text": "Python",
"alias_type": "CANONICAL",
"id": 67,
"is_primary": true,
"match_strategy": "CASE_INSENSITIVE"
},
{
"alias_text": "Python 2",
"alias_type": "VERSION",
"id": 72,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
},
{
"alias_text": "Python 2.x",
"alias_type": "VERSION",
"id": 74,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
},
{
"alias_text": "Python 3",
"alias_type": "VERSION",
"id": 73,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
},
{
"alias_text": "Python 3.10",
"alias_type": "VERSION",
"id": 76,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
},
{
"alias_text": "Python 3.11",
"alias_type": "VERSION",
"id": 77,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
},
{
"alias_text": "Python 3.12",
"alias_type": "VERSION",
"id": 78,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
},
{
"alias_text": "Python 3.x",
"alias_type": "VERSION",
"id": 75,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
},
{
"alias_text": "py",
"alias_type": "VERSION",
"id": 2183,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
},
{
"alias_text": "py2",
"alias_type": "VERSION",
"id": 68,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
},
{
"alias_text": "py3",
"alias_type": "VERSION",
"id": 69,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
},
{
"alias_text": "python 3",
"alias_type": "VERSION",
"id": 2186,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
},
{
"alias_text": "python 3.x",
"alias_type": "VERSION",
"id": 2849,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
},
{
"alias_text": "python2",
"alias_type": "VERSION",
"id": 70,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
},
{
"alias_text": "python3",
"alias_type": "VERSION",
"id": 71,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
},
{
"alias_text": "python3.x",
"alias_type": "VERSION",
"id": 2848,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
}
],
"canonical": {
"category_id": 6,
"display_name": "Python",
"id": 5,
"is_also_category": false,
"is_extractable": true,
"skill_nature": "LANGUAGE",
"slug": "python",
"sub_category_id": 96,
"typical_lifespan": "EVERGREEN",
"volatility": "STABLE"
},
"dimensions": [
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Cloud Security Scripting \u0026 DSL Languages",
"id": 248,
"rationale": "Proficiency in programming and domain-specific languages used to automate and script cloud security controls.",
"slug": "cloud-security-scripting-dsl-languages",
"source": "db"
},
"input_skill": "Python",
"llm_role": null,
"roles_from_db": [
{
"display_name": "Cloud Security Engineer",
"id": 23,
"rationale": null,
"role_archetype": null,
"slug": "cloud-security-engineer",
"source": "db"
}
]
},
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Programming Languages",
"id": 1,
"rationale": "Primary implementation languages used to build client and server feature code. Full stack engineers need enough fluency to move across layers and implement product behavior end to end.",
"slug": "programming-languages",
"source": "db"
},
"input_skill": "Python",
"llm_role": null,
"roles_from_db": [
{
"display_name": "Backend Developer",
"id": 1,
"rationale": null,
"role_archetype": "A Backend Engineer designs, builds, and maintains the server-side logic and data handling that power applications and services. They focus on implementing reliable business functionality, integrating with other systems, and ensuring the backend is scalable, maintainable, and observable.",
"slug": "backend-engineer",
"source": "db"
},
{
"display_name": "Fullstack Developer",
"id": 15,
"rationale": null,
"role_archetype": null,
"slug": "full-stack-engineer",
"source": "db"
}
]
},
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Programming Languages and Scripting",
"id": 59,
"rationale": "Languages used to write security automation, analysis scripts, detection logic, and remediation helpers. This is the primary implementation surface for a cybersecurity engineer across tooling and response workflows.",
"slug": "programming-languages-and-scripting",
"source": "db"
},
"input_skill": "Python",
"llm_role": null,
"roles_from_db": [
{
"display_name": "Cyber Security Engineer",
"id": 5,
"rationale": null,
"role_archetype": null,
"slug": "cybersecurity-engineer",
"source": "db"
}
]
},
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Programming Languages for Data Work",
"id": 21,
"rationale": "Languages used to implement data pipelines, transformations, and operational glue. This is the primary coding surface for building ingestion, enrichment, and automation logic in data engineering.",
"slug": "programming-languages-for-data-work",
"source": "db"
},
"input_skill": "Python",
"llm_role": null,
"roles_from_db": [
{
"display_name": "Data Engineer",
"id": 2,
"rationale": null,
"role_archetype": null,
"slug": "data-engineer",
"source": "db"
}
]
},
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Programming Languages for ML Systems",
"id": 39,
"rationale": "Languages used to build training code, inference services, evaluation jobs, and ML glue code. This is the primary implementation surface for ML engineers across experimentation and productionization.",
"slug": "programming-languages-for-ml-systems",
"source": "db"
},
"input_skill": "Python",
"llm_role": null,
"roles_from_db": [
{
"display_name": "ML Engineer",
"id": 3,
"rationale": null,
"role_archetype": null,
"slug": "ml-engineer",
"source": "db"
},
{
"display_name": "MLOps Engineer",
"id": 16,
"rationale": null,
"role_archetype": null,
"slug": "ml-ops-engineer",
"source": "db"
}
]
},
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Programming Languages for XR",
"id": 97,
"rationale": "Primary implementation languages used to build immersive client features, interaction logic, and device-specific runtime behavior. This is the core coding surface for AR/VR experiences.",
"slug": "programming-languages-for-xr",
"source": "db"
},
"input_skill": "Python",
"llm_role": null,
"roles_from_db": [
{
"display_name": "AR/VR Engineer",
"id": 8,
"rationale": null,
"role_archetype": null,
"slug": "ar-vr-engineer",
"source": "db"
}
]
},
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Python Programming",
"id": 290,
"rationale": "Core Python language skills used to implement backend business logic, request handlers, integrations, and service internals. This is the primary coding surface for the role.",
"slug": "python-programming",
"source": "db"
},
"input_skill": "Python",
"llm_role": null,
"roles_from_db": [
{
"display_name": "Python Backend Developer",
"id": 80,
"rationale": null,
"role_archetype": "Engineering",
"slug": "python-backend-developer",
"source": "db"
}
]
}
],
"input_skill": "Python",
"matched_via": "alias",
"new_alias_persisted": false,
"new_alias_text": null,
"new_skill_meta": null,
"source_tag": "db",
"was_in_llm_skills": true
},
{
"aliases_in_db": [
{
"alias_text": "Java",
"alias_type": "CANONICAL",
"id": 1,
"is_primary": true,
"match_strategy": "CASE_INSENSITIVE"
},
{
"alias_text": "JDK",
"alias_type": "VERSION",
"id": 2968,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
},
{
"alias_text": "JDK 10",
"alias_type": "VERSION",
"id": 2194,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
},
{
"alias_text": "JDK 11",
"alias_type": "VERSION",
"id": 4,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
},
{
"alias_text": "JDK 12",
"alias_type": "VERSION",
"id": 2196,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
},
{
"alias_text": "JDK 13",
"alias_type": "VERSION",
"id": 2197,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
},
{
"alias_text": "JDK 14",
"alias_type": "VERSION",
"id": 2198,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
},
{
"alias_text": "JDK 15",
"alias_type": "VERSION",
"id": 2199,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
},
{
"alias_text": "JDK 16",
"alias_type": "VERSION",
"id": 2200,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
},
{
"alias_text": "JDK 17",
"alias_type": "VERSION",
"id": 5,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
},
{
"alias_text": "JDK 18",
"alias_type": "VERSION",
"id": 2202,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
},
{
"alias_text": "JDK 19",
"alias_type": "VERSION",
"id": 2203,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
},
{
"alias_text": "JDK 20",
"alias_type": "VERSION",
"id": 2204,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
},
{
"alias_text": "JDK 21",
"alias_type": "VERSION",
"id": 6,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
},
{
"alias_text": "JDK 5",
"alias_type": "VERSION",
"id": 2189,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
},
{
"alias_text": "JDK 6",
"alias_type": "VERSION",
"id": 2190,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
},
{
"alias_text": "JDK 7",
"alias_type": "VERSION",
"id": 2191,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
},
{
"alias_text": "JDK 8",
"alias_type": "VERSION",
"id": 3,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
},
{
"alias_text": "JDK 9",
"alias_type": "VERSION",
"id": 2193,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
},
{
"alias_text": "Java 1.0",
"alias_type": "VERSION",
"id": 11,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
},
{
"alias_text": "Java 1.1",
"alias_type": "VERSION",
"id": 12,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
},
{
"alias_text": "Java 1.2",
"alias_type": "VERSION",
"id": 13,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
},
{
"alias_text": "Java 1.3",
"alias_type": "VERSION",
"id": 14,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
},
{
"alias_text": "Java 1.4",
"alias_type": "VERSION",
"id": 15,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
},
{
"alias_text": "Java 1.5",
"alias_type": "VERSION",
"id": 16,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
},
{
"alias_text": "Java 1.6",
"alias_type": "VERSION",
"id": 17,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
},
{
"alias_text": "Java 1.7",
"alias_type": "VERSION",
"id": 18,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
},
{
"alias_text": "Java 1.8",
"alias_type": "VERSION",
"id": 19,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
},
{
"alias_text": "Java 10",
"alias_type": "VERSION",
"id": 2211,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
},
{
"alias_text": "Java 11",
"alias_type": "VERSION",
"id": 8,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
},
{
"alias_text": "Java 12",
"alias_type": "VERSION",
"id": 2213,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
},
{
"alias_text": "Java 13",
"alias_type": "VERSION",
"id": 2214,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
},
{
"alias_text": "Java 14",
"alias_type": "VERSION",
"id": 2215,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
},
{
"alias_text": "Java 15",
"alias_type": "VERSION",
"id": 2216,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
},
{
"alias_text": "Java 16",
"alias_type": "VERSION",
"id": 2217,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
},
{
"alias_text": "Java 17",
"alias_type": "VERSION",
"id": 9,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
},
{
"alias_text": "Java 18",
"alias_type": "VERSION",
"id": 2219,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
},
{
"alias_text": "Java 19",
"alias_type": "VERSION",
"id": 2220,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
},
{
"alias_text": "Java 20",
"alias_type": "VERSION",
"id": 2221,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
},
{
"alias_text": "Java 21",
"alias_type": "VERSION",
"id": 10,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
},
{
"alias_text": "Java 5",
"alias_type": "VERSION",
"id": 288,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
},
{
"alias_text": "Java 6",
"alias_type": "VERSION",
"id": 289,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
},
{
"alias_text": "Java 7",
"alias_type": "VERSION",
"id": 290,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
},
{
"alias_text": "Java 8",
"alias_type": "VERSION",
"id": 7,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
},
{
"alias_text": "Java 9",
"alias_type": "VERSION",
"id": 2210,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
},
{
"alias_text": "Java11",
"alias_type": "VERSION",
"id": 2976,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
},
{
"alias_text": "Java17",
"alias_type": "VERSION",
"id": 2977,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
},
{
"alias_text": "Java21",
"alias_type": "VERSION",
"id": 2978,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
},
{
"alias_text": "Java8",
"alias_type": "VERSION",
"id": 2971,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
},
{
"alias_text": "OpenJDK 11",
"alias_type": "VERSION",
"id": 21,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
},
{
"alias_text": "OpenJDK 17",
"alias_type": "VERSION",
"id": 22,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
},
{
"alias_text": "OpenJDK 21",
"alias_type": "VERSION",
"id": 23,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
},
{
"alias_text": "OpenJDK 8",
"alias_type": "VERSION",
"id": 20,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
},
{
"alias_text": "java 11",
"alias_type": "VERSION",
"id": 1512,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
},
{
"alias_text": "java 17",
"alias_type": "VERSION",
"id": 1513,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
},
{
"alias_text": "java 21",
"alias_type": "VERSION",
"id": 1514,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
},
{
"alias_text": "java 4",
"alias_type": "VERSION",
"id": 1496,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
},
{
"alias_text": "java 5",
"alias_type": "VERSION",
"id": 1497,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
},
{
"alias_text": "java 6",
"alias_type": "VERSION",
"id": 1498,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
},
{
"alias_text": "java 7",
"alias_type": "VERSION",
"id": 1499,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
},
{
"alias_text": "java 8",
"alias_type": "VERSION",
"id": 1500,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
},
{
"alias_text": "java lts",
"alias_type": "VERSION",
"id": 3122,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
},
{
"alias_text": "java-11",
"alias_type": "VERSION",
"id": 1515,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
},
{
"alias_text": "java-17",
"alias_type": "VERSION",
"id": 1516,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
},
{
"alias_text": "java-21",
"alias_type": "VERSION",
"id": 1517,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
},
{
"alias_text": "java-4",
"alias_type": "VERSION",
"id": 1501,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
},
{
"alias_text": "java-5",
"alias_type": "VERSION",
"id": 1502,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
},
{
"alias_text": "java-6",
"alias_type": "VERSION",
"id": 1503,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
},
{
"alias_text": "java-7",
"alias_type": "VERSION",
"id": 1504,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
},
{
"alias_text": "java-8",
"alias_type": "VERSION",
"id": 1505,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
},
{
"alias_text": "java11",
"alias_type": "VERSION",
"id": 1506,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
},
{
"alias_text": "java17",
"alias_type": "VERSION",
"id": 1507,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
},
{
"alias_text": "java21",
"alias_type": "VERSION",
"id": 1508,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
},
{
"alias_text": "java4",
"alias_type": "VERSION",
"id": 1482,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
},
{
"alias_text": "java5",
"alias_type": "VERSION",
"id": 1483,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
},
{
"alias_text": "java6",
"alias_type": "VERSION",
"id": 1484,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
},
{
"alias_text": "java7",
"alias_type": "VERSION",
"id": 1485,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
},
{
"alias_text": "java8",
"alias_type": "VERSION",
"id": 1486,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
},
{
"alias_text": "jdk 11",
"alias_type": "VERSION",
"id": 1509,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
},
{
"alias_text": "jdk 17",
"alias_type": "VERSION",
"id": 1510,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
},
{
"alias_text": "jdk 21",
"alias_type": "VERSION",
"id": 1511,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
},
{
"alias_text": "jdk 4",
"alias_type": "VERSION",
"id": 1487,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
},
{
"alias_text": "jdk 5",
"alias_type": "VERSION",
"id": 1488,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
},
{
"alias_text": "jdk 6",
"alias_type": "VERSION",
"id": 1489,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
},
{
"alias_text": "jdk 7",
"alias_type": "VERSION",
"id": 1490,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
},
{
"alias_text": "jdk 8",
"alias_type": "VERSION",
"id": 1491,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
},
{
"alias_text": "jdk11",
"alias_type": "VERSION",
"id": 1492,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
},
{
"alias_text": "jdk17",
"alias_type": "VERSION",
"id": 1493,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
},
{
"alias_text": "jdk21",
"alias_type": "VERSION",
"id": 1494,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
},
{
"alias_text": "jdk4",
"alias_type": "VERSION",
"id": 1477,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
},
{
"alias_text": "jdk5",
"alias_type": "VERSION",
"id": 1478,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
},
{
"alias_text": "jdk6",
"alias_type": "VERSION",
"id": 1479,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
},
{
"alias_text": "jdk7",
"alias_type": "VERSION",
"id": 1480,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
},
{
"alias_text": "jdk8",
"alias_type": "VERSION",
"id": 1481,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
},
{
"alias_text": "jvm21",
"alias_type": "VERSION",
"id": 1495,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
}
],
"canonical": {
"category_id": 6,
"display_name": "Java",
"id": 1,
"is_also_category": false,
"is_extractable": true,
"skill_nature": "LANGUAGE",
"slug": "java",
"sub_category_id": 96,
"typical_lifespan": "EVERGREEN",
"volatility": "STABLE"
},
"dimensions": [
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Java Language and JVM",
"id": 279,
"rationale": "Core Java implementation skills used to build backend service logic, utilities, and internal abstractions. This is the primary coding surface for the role and includes language features plus JVM behavior that affect correctness and maintainability.",
"slug": "java-language-and-jvm",
"source": "db"
},
"input_skill": "Java",
"llm_role": null,
"roles_from_db": [
{
"display_name": "Java Backend Developer",
"id": 79,
"rationale": null,
"role_archetype": "Engineering",
"slug": "java-backend-developer",
"source": "db"
},
{
"display_name": "Kotlin Backend Developer",
"id": 84,
"rationale": null,
"role_archetype": "Engineering",
"slug": "kotlin-server-backend-developer",
"source": "db"
},
{
"display_name": "Scala Backend Developer",
"id": 87,
"rationale": null,
"role_archetype": "Engineering",
"slug": "scala-backend-developer",
"source": "db"
}
]
},
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Kotlin and Java",
"id": 161,
"rationale": "Primary implementation languages for Android app features, platform integration, and client-side business logic. Android engineers use these languages to build screens, state flows, service adapters, and device-aware behavior.",
"slug": "kotlin-and-java",
"source": "db"
},
"input_skill": "Java",
"llm_role": null,
"roles_from_db": [
{
"display_name": "Android Developer",
"id": 4,
"rationale": null,
"role_archetype": null,
"slug": "android-engineer",
"source": "db"
}
]
},
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Native Mobile Languages",
"id": 274,
"rationale": "Primary implementation languages used to build platform-specific app features, UI logic, and device integrations. This is the core coding surface for native mobile work on one platform.",
"slug": "native-mobile-languages",
"source": "db"
},
"input_skill": "Java",
"llm_role": null,
"roles_from_db": [
{
"display_name": "Native Mobile Developer",
"id": 75,
"rationale": null,
"role_archetype": "Engineering",
"slug": "native-mobile-developer",
"source": "db"
}
]
},
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Pega Programming Languages \u0026 DSLs",
"id": 267,
"rationale": "Programming languages and domain-specific languages used in Pega development.",
"slug": "pega-programming-languages-dsls",
"source": "db"
},
"input_skill": "Java",
"llm_role": null,
"roles_from_db": [
{
"display_name": "Pega Developer",
"id": 24,
"rationale": null,
"role_archetype": null,
"slug": "pega-developer",
"source": "db"
}
]
},
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Programming Languages",
"id": 1,
"rationale": "Primary implementation languages used to build client and server feature code. Full stack engineers need enough fluency to move across layers and implement product behavior end to end.",
"slug": "programming-languages",
"source": "db"
},
"input_skill": "Java",
"llm_role": null,
"roles_from_db": [
{
"display_name": "Backend Developer",
"id": 1,
"rationale": null,
"role_archetype": "A Backend Engineer designs, builds, and maintains the server-side logic and data handling that power applications and services. They focus on implementing reliable business functionality, integrating with other systems, and ensuring the backend is scalable, maintainable, and observable.",
"slug": "backend-engineer",
"source": "db"
},
{
"display_name": "Fullstack Developer",
"id": 15,
"rationale": null,
"role_archetype": null,
"slug": "full-stack-engineer",
"source": "db"
}
]
},
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Programming Languages for Data Work",
"id": 21,
"rationale": "Languages used to implement data pipelines, transformations, and operational glue. This is the primary coding surface for building ingestion, enrichment, and automation logic in data engineering.",
"slug": "programming-languages-for-data-work",
"source": "db"
},
"input_skill": "Java",
"llm_role": null,
"roles_from_db": [
{
"display_name": "Data Engineer",
"id": 2,
"rationale": null,
"role_archetype": null,
"slug": "data-engineer",
"source": "db"
}
]
}
],
"input_skill": "Java",
"matched_via": "alias",
"new_alias_persisted": false,
"new_alias_text": null,
"new_skill_meta": null,
"source_tag": "db",
"was_in_llm_skills": true
},
{
"aliases_in_db": [
{
"alias_text": "Apache Spark",
"alias_type": "CANONICAL",
"id": 2004,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
},
{
"alias_text": "apache spark 3",
"alias_type": "VERSION",
"id": 2006,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
},
{
"alias_text": "spark",
"alias_type": "VERSION",
"id": 2510,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
},
{
"alias_text": "spark 3",
"alias_type": "VERSION",
"id": 2007,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
},
{
"alias_text": "spark 3.x",
"alias_type": "VERSION",
"id": 2009,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
},
{
"alias_text": "spark3",
"alias_type": "VERSION",
"id": 2008,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
}
],
"canonical": {
"category_id": 5,
"display_name": "Apache Spark",
"id": 1350,
"is_also_category": false,
"is_extractable": true,
"skill_nature": "FRAMEWORK",
"slug": "apache-spark",
"sub_category_id": 1021,
"typical_lifespan": "EVERGREEN",
"volatility": "STABLE"
},
"dimensions": [
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "ETL and ELT Tooling",
"id": 24,
"rationale": "Packaged tools for extracting, loading, and transforming data across systems. This dimension covers connector-based ingestion, transformation frameworks, and managed integration products.",
"slug": "etl-and-elt-tooling",
"source": "db"
},
"input_skill": "PySpark",
"llm_role": null,
"roles_from_db": [
{
"display_name": "Data Engineer",
"id": 2,
"rationale": null,
"role_archetype": null,
"slug": "data-engineer",
"source": "db"
}
]
}
],
"input_skill": "PySpark",
"matched_via": "embedding_alias",
"new_alias_persisted": false,
"new_alias_text": null,
"new_skill_meta": null,
"source_tag": "db",
"was_in_llm_skills": true
},
{
"aliases_in_db": [
{
"alias_text": "Apache Spark",
"alias_type": "CANONICAL",
"id": 2004,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
},
{
"alias_text": "apache spark 3",
"alias_type": "VERSION",
"id": 2006,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
},
{
"alias_text": "spark",
"alias_type": "VERSION",
"id": 2510,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
},
{
"alias_text": "spark 3",
"alias_type": "VERSION",
"id": 2007,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
},
{
"alias_text": "spark 3.x",
"alias_type": "VERSION",
"id": 2009,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
},
{
"alias_text": "spark3",
"alias_type": "VERSION",
"id": 2008,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
}
],
"canonical": {
"category_id": 5,
"display_name": "Apache Spark",
"id": 1350,
"is_also_category": false,
"is_extractable": true,
"skill_nature": "FRAMEWORK",
"slug": "apache-spark",
"sub_category_id": 1021,
"typical_lifespan": "EVERGREEN",
"volatility": "STABLE"
},
"dimensions": [
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "ETL and ELT Tooling",
"id": 24,
"rationale": "Packaged tools for extracting, loading, and transforming data across systems. This dimension covers connector-based ingestion, transformation frameworks, and managed integration products.",
"slug": "etl-and-elt-tooling",
"source": "db"
},
"input_skill": "Spark",
"llm_role": null,
"roles_from_db": [
{
"display_name": "Data Engineer",
"id": 2,
"rationale": null,
"role_archetype": null,
"slug": "data-engineer",
"source": "db"
}
]
}
],
"input_skill": "Spark",
"matched_via": "alias",
"new_alias_persisted": false,
"new_alias_text": null,
"new_skill_meta": null,
"source_tag": "db",
"was_in_llm_skills": true
},
{
"aliases_in_db": [
{
"alias_text": "Scala",
"alias_type": "CANONICAL",
"id": 272,
"is_primary": true,
"match_strategy": "CASE_INSENSITIVE"
}
],
"canonical": {
"category_id": 6,
"display_name": "Scala",
"id": 102,
"is_also_category": false,
"is_extractable": true,
"skill_nature": "LANGUAGE",
"slug": "scala",
"sub_category_id": 96,
"typical_lifespan": "EVERGREEN",
"volatility": "STABLE"
},
"dimensions": [
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Programming Languages for Data Work",
"id": 21,
"rationale": "Languages used to implement data pipelines, transformations, and operational glue. This is the primary coding surface for building ingestion, enrichment, and automation logic in data engineering.",
"slug": "programming-languages-for-data-work",
"source": "db"
},
"input_skill": "Scala",
"llm_role": null,
"roles_from_db": [
{
"display_name": "Data Engineer",
"id": 2,
"rationale": null,
"role_archetype": null,
"slug": "data-engineer",
"source": "db"
}
]
},
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Programming Languages for ML Systems",
"id": 39,
"rationale": "Languages used to build training code, inference services, evaluation jobs, and ML glue code. This is the primary implementation surface for ML engineers across experimentation and productionization.",
"slug": "programming-languages-for-ml-systems",
"source": "db"
},
"input_skill": "Scala",
"llm_role": null,
"roles_from_db": [
{
"display_name": "ML Engineer",
"id": 3,
"rationale": null,
"role_archetype": null,
"slug": "ml-engineer",
"source": "db"
},
{
"display_name": "MLOps Engineer",
"id": 16,
"rationale": null,
"role_archetype": null,
"slug": "ml-ops-engineer",
"source": "db"
}
]
}
],
"input_skill": "Scala",
"matched_via": "alias",
"new_alias_persisted": false,
"new_alias_text": null,
"new_skill_meta": null,
"source_tag": "db",
"was_in_llm_skills": true
},
{
"aliases_in_db": [
{
"alias_text": "Hadoop",
"alias_type": "CANONICAL",
"id": 2010,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
}
],
"canonical": {
"category_id": 5,
"display_name": "Hadoop",
"id": 1351,
"is_also_category": false,
"is_extractable": true,
"skill_nature": "FRAMEWORK",
"slug": "hadoop",
"sub_category_id": 91,
"typical_lifespan": "EVERGREEN",
"volatility": "STABLE"
},
"dimensions": [
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "ETL and ELT Tooling",
"id": 24,
"rationale": "Packaged tools for extracting, loading, and transforming data across systems. This dimension covers connector-based ingestion, transformation frameworks, and managed integration products.",
"slug": "etl-and-elt-tooling",
"source": "db"
},
"input_skill": "Hadoop",
"llm_role": null,
"roles_from_db": [
{
"display_name": "Data Engineer",
"id": 2,
"rationale": null,
"role_archetype": null,
"slug": "data-engineer",
"source": "db"
}
]
}
],
"input_skill": "Hadoop",
"matched_via": "alias",
"new_alias_persisted": false,
"new_alias_text": null,
"new_skill_meta": null,
"source_tag": "db",
"was_in_llm_skills": true
},
{
"aliases_in_db": [],
"canonical": null,
"dimensions": [],
"input_skill": "HDFS",
"matched_via": null,
"new_alias_persisted": false,
"new_alias_text": null,
"new_skill_meta": {
"derived": {
"category": "Data Engineering Tools",
"skill_nature": "TOOL",
"sub_category": "general",
"typical_lifespan": "MULTI_YEAR",
"version_strategy": "UNVERSIONED",
"volatility": "MEDIUM"
},
"enrichment": null,
"keep_log": [],
"locked_dimensions": [],
"merge_log": [],
"placed": null,
"relationships": null,
"skill_id": "hdfs",
"split_log": [],
"typed": null,
"warnings": []
},
"source_tag": "llm",
"was_in_llm_skills": true
},
{
"aliases_in_db": [
{
"alias_text": "Bash",
"alias_type": "VERSION",
"id": 273,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
},
{
"alias_text": "Bash 3.x",
"alias_type": "VERSION",
"id": 279,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
},
{
"alias_text": "Bash 4.x",
"alias_type": "VERSION",
"id": 280,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
},
{
"alias_text": "Bash 5.x",
"alias_type": "VERSION",
"id": 281,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
},
{
"alias_text": "GNU Bash",
"alias_type": "VERSION",
"id": 282,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
},
{
"alias_text": "bash",
"alias_type": "VERSION",
"id": 275,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
},
{
"alias_text": "bash 3",
"alias_type": "VERSION",
"id": 276,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
},
{
"alias_text": "bash 3.x",
"alias_type": "VERSION",
"id": 283,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
},
{
"alias_text": "bash 4",
"alias_type": "VERSION",
"id": 277,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
},
{
"alias_text": "bash 4.x",
"alias_type": "VERSION",
"id": 284,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
},
{
"alias_text": "bash 5",
"alias_type": "VERSION",
"id": 278,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
},
{
"alias_text": "bash 5.x",
"alias_type": "VERSION",
"id": 285,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
}
],
"canonical": {
"category_id": 6,
"display_name": "Bash",
"id": 103,
"is_also_category": false,
"is_extractable": true,
"skill_nature": "LANGUAGE",
"slug": "bash",
"sub_category_id": 238,
"typical_lifespan": "EVERGREEN",
"volatility": "STABLE"
},
"dimensions": [
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Programming Languages and Scripting",
"id": 59,
"rationale": "Languages used to write security automation, analysis scripts, detection logic, and remediation helpers. This is the primary implementation surface for a cybersecurity engineer across tooling and response workflows.",
"slug": "programming-languages-and-scripting",
"source": "db"
},
"input_skill": "Bash",
"llm_role": null,
"roles_from_db": [
{
"display_name": "Cyber Security Engineer",
"id": 5,
"rationale": null,
"role_archetype": null,
"slug": "cybersecurity-engineer",
"source": "db"
}
]
},
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Programming Languages for Data Work",
"id": 21,
"rationale": "Languages used to implement data pipelines, transformations, and operational glue. This is the primary coding surface for building ingestion, enrichment, and automation logic in data engineering.",
"slug": "programming-languages-for-data-work",
"source": "db"
},
"input_skill": "Bash",
"llm_role": null,
"roles_from_db": [
{
"display_name": "Data Engineer",
"id": 2,
"rationale": null,
"role_archetype": null,
"slug": "data-engineer",
"source": "db"
}
]
}
],
"input_skill": "Bash",
"matched_via": "alias",
"new_alias_persisted": false,
"new_alias_text": null,
"new_skill_meta": null,
"source_tag": "db",
"was_in_llm_skills": true
},
{
"aliases_in_db": [],
"canonical": null,
"dimensions": [],
"input_skill": "UNIX",
"matched_via": null,
"new_alias_persisted": false,
"new_alias_text": null,
"new_skill_meta": {
"derived": {
"category": "Operating Systems",
"skill_nature": "PLATFORM",
"sub_category": "general",
"typical_lifespan": "EVERGREEN",
"version_strategy": "UNVERSIONED",
"volatility": "STABLE"
},
"enrichment": null,
"keep_log": [],
"locked_dimensions": [],
"merge_log": [],
"placed": null,
"relationships": null,
"skill_id": "unix",
"split_log": [],
"typed": null,
"warnings": []
},
"source_tag": "llm",
"was_in_llm_skills": true
},
{
"aliases_in_db": [
{
"alias_text": "Hive",
"alias_type": "CANONICAL",
"id": 4198,
"is_primary": true,
"match_strategy": "CASE_INSENSITIVE"
}
],
"canonical": {
"category_id": 3,
"display_name": "Hive",
"id": 2754,
"is_also_category": false,
"is_extractable": true,
"skill_nature": "TOOL",
"slug": "hive",
"sub_category_id": 2242,
"typical_lifespan": "EVERGREEN",
"volatility": "STABLE"
},
"dimensions": [
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Local Persistence and Offline Behavior",
"id": 85,
"rationale": "On-device storage used for caching, offline support, and durable client state. This cluster is coherent because iOS apps often need to preserve user progress and data when connectivity is limited.",
"slug": "local-persistence-and-offline-behavior",
"source": "db"
},
"input_skill": "Hive",
"llm_role": null,
"roles_from_db": [
{
"display_name": "Android Developer",
"id": 4,
"rationale": null,
"role_archetype": null,
"slug": "android-engineer",
"source": "db"
},
{
"display_name": "Flutter Developer",
"id": 74,
"rationale": null,
"role_archetype": "Engineering",
"slug": "flutter-developer",
"source": "db"
},
{
"display_name": "Hybrid Mobile Developer",
"id": 11,
"rationale": null,
"role_archetype": null,
"slug": "hybrid-mobile-developer",
"source": "db"
},
{
"display_name": "Native Mobile Developer",
"id": 75,
"rationale": null,
"role_archetype": "Engineering",
"slug": "native-mobile-developer",
"source": "db"
},
{
"display_name": "React Native Developer",
"id": 73,
"rationale": null,
"role_archetype": "Engineering",
"slug": "react-native-developer",
"source": "db"
},
{
"display_name": "iOS Developer",
"id": 6,
"rationale": null,
"role_archetype": null,
"slug": "ios-engineer",
"source": "db"
}
]
}
],
"input_skill": "Hive",
"matched_via": "alias",
"new_alias_persisted": false,
"new_alias_text": null,
"new_skill_meta": null,
"source_tag": "db",
"was_in_llm_skills": true
},
{
"aliases_in_db": [
{
"alias_text": "Cassandra",
"alias_type": "CANONICAL",
"id": 2013,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
}
],
"canonical": {
"category_id": 3,
"display_name": "Cassandra",
"id": 1354,
"is_also_category": false,
"is_extractable": true,
"skill_nature": "TOOL",
"slug": "cassandra",
"sub_category_id": 31,
"typical_lifespan": "EVERGREEN",
"volatility": "STABLE"
},
"dimensions": [
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Cloud Storage and Data Services",
"id": 144,
"rationale": "Cloud-native storage and managed data services used to place workloads, choose durability tiers, and define platform boundaries. This is a coherent cluster because architects evaluate storage fit, access patterns, and managed service tradeoffs.",
"slug": "cloud-storage-and-data-services",
"source": "db"
},
"input_skill": "Cassandra",
"llm_role": null,
"roles_from_db": [
{
"display_name": "Cloud Architect",
"id": 9,
"rationale": null,
"role_archetype": null,
"slug": "cloud-architect",
"source": "db"
}
]
}
],
"input_skill": "Cassandra",
"matched_via": "alias",
"new_alias_persisted": false,
"new_alias_text": null,
"new_skill_meta": null,
"source_tag": "db",
"was_in_llm_skills": true
},
{
"aliases_in_db": [],
"canonical": null,
"dimensions": [],
"input_skill": "Pig",
"matched_via": null,
"new_alias_persisted": false,
"new_alias_text": null,
"new_skill_meta": {
"derived": {
"category": "Data Engineering Tools",
"skill_nature": "TOOL",
"sub_category": "general",
"typical_lifespan": "MULTI_YEAR",
"version_strategy": "UNVERSIONED",
"volatility": "MEDIUM"
},
"enrichment": null,
"keep_log": [],
"locked_dimensions": [],
"merge_log": [],
"placed": null,
"relationships": null,
"skill_id": "pig",
"split_log": [],
"typed": null,
"warnings": []
},
"source_tag": "llm",
"was_in_llm_skills": true
},
{
"aliases_in_db": [
{
"alias_text": "MySQL",
"alias_type": "CANONICAL",
"id": 134,
"is_primary": true,
"match_strategy": "CASE_INSENSITIVE"
}
],
"canonical": {
"category_id": 3,
"display_name": "MySQL",
"id": 17,
"is_also_category": false,
"is_extractable": true,
"skill_nature": "TOOL",
"slug": "mysql",
"sub_category_id": 29,
"typical_lifespan": "EVERGREEN",
"volatility": "STABLE"
},
"dimensions": [
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Relational Data Modeling",
"id": 216,
"rationale": "Modeling and tuning relational persistence for backend features. PHP backend developers need this to shape schemas, indexes, transactions, and query-aware data structures that support application behavior.",
"slug": "relational-data-modeling",
"source": "db"
},
"input_skill": "MySQL",
"llm_role": null,
"roles_from_db": [
{
"display_name": "Fullstack Developer",
"id": 15,
"rationale": null,
"role_archetype": null,
"slug": "full-stack-engineer",
"source": "db"
},
{
"display_name": "PHP Backend Developer",
"id": 86,
"rationale": null,
"role_archetype": "Engineering",
"slug": "php-backend-developer",
"source": "db"
}
]
},
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Relational Database Design",
"id": 4,
"rationale": "Modeling and operating relational persistence for backend services. Includes schema design, normalization, indexing, transactions, and query tuning for operational data stores.",
"slug": "relational-database-design",
"source": "db"
},
"input_skill": "MySQL",
"llm_role": null,
"roles_from_db": [
{
"display_name": ".NET Backend Developer",
"id": 83,
"rationale": null,
"role_archetype": "Engineering",
"slug": "dotnet-backend-developer",
"source": "db"
},
{
"display_name": "Backend Developer",
"id": 1,
"rationale": null,
"role_archetype": "A Backend Engineer designs, builds, and maintains the server-side logic and data handling that power applications and services. They focus on implementing reliable business functionality, integrating with other systems, and ensuring the backend is scalable, maintainable, and observable.",
"slug": "backend-engineer",
"source": "db"
},
{
"display_name": "Kotlin Backend Developer",
"id": 84,
"rationale": null,
"role_archetype": "Engineering",
"slug": "kotlin-server-backend-developer",
"source": "db"
},
{
"display_name": "Node.js Backend Developer",
"id": 82,
"rationale": null,
"role_archetype": "Engineering",
"slug": "node-backend-developer",
"source": "db"
},
{
"display_name": "Python Backend Developer",
"id": 80,
"rationale": null,
"role_archetype": "Engineering",
"slug": "python-backend-developer",
"source": "db"
},
{
"display_name": "Ruby Backend Developer",
"id": 85,
"rationale": null,
"role_archetype": "Engineering",
"slug": "ruby-backend-developer",
"source": "db"
},
{
"display_name": "Scala Backend Developer",
"id": 87,
"rationale": null,
"role_archetype": "Engineering",
"slug": "scala-backend-developer",
"source": "db"
}
]
},
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Relational Database Usage",
"id": 371,
"rationale": "Working effectively with operational relational databases from Go backend services. This includes schema-aware querying, indexing awareness, transactions, and understanding how service code interacts with PostgreSQL or similar systems.",
"slug": "relational-database-usage",
"source": "db"
},
"input_skill": "MySQL",
"llm_role": null,
"roles_from_db": [
{
"display_name": "Go Backend Developer",
"id": 81,
"rationale": null,
"role_archetype": "Engineering",
"slug": "go-backend-developer",
"source": "db"
}
]
}
],
"input_skill": "MySQL",
"matched_via": "alias",
"new_alias_persisted": false,
"new_alias_text": null,
"new_skill_meta": null,
"source_tag": "db",
"was_in_llm_skills": true
},
{
"aliases_in_db": [
{
"alias_text": "NoSQL",
"alias_type": "CANONICAL",
"id": 1989,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
}
],
"canonical": {
"category_id": 2,
"display_name": "NoSQL",
"id": 1346,
"is_also_category": false,
"is_extractable": true,
"skill_nature": "CONCEPT",
"slug": "nosql",
"sub_category_id": 1019,
"typical_lifespan": "EVERGREEN",
"volatility": "STABLE"
},
"dimensions": [
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "NoSQL Databases",
"id": 19,
"rationale": "Models and manages data using non-relational database systems.",
"slug": "nosql-databases",
"source": "db"
},
"input_skill": "NoSQL",
"llm_role": null,
"roles_from_db": [
{
"display_name": "Backend Developer",
"id": 1,
"rationale": null,
"role_archetype": "A Backend Engineer designs, builds, and maintains the server-side logic and data handling that power applications and services. They focus on implementing reliable business functionality, integrating with other systems, and ensuring the backend is scalable, maintainable, and observable.",
"slug": "backend-engineer",
"source": "db"
}
]
}
],
"input_skill": "NoSQL",
"matched_via": "alias",
"new_alias_persisted": false,
"new_alias_text": null,
"new_skill_meta": null,
"source_tag": "db",
"was_in_llm_skills": true
},
{
"aliases_in_db": [],
"canonical": null,
"dimensions": [],
"input_skill": "ETL",
"matched_via": null,
"new_alias_persisted": false,
"new_alias_text": null,
"new_skill_meta": {
"derived": {
"category": "Data Engineering Tools",
"skill_nature": "PRACTICE",
"sub_category": "general",
"typical_lifespan": "MULTI_YEAR",
"version_strategy": "UNVERSIONED",
"volatility": "MEDIUM"
},
"enrichment": null,
"keep_log": [],
"locked_dimensions": [],
"merge_log": [],
"placed": null,
"relationships": null,
"skill_id": "etl",
"split_log": [],
"typed": null,
"warnings": []
},
"source_tag": "llm",
"was_in_llm_skills": true
},
{
"aliases_in_db": [],
"canonical": null,
"dimensions": [],
"input_skill": "Data Science",
"matched_via": null,
"new_alias_persisted": false,
"new_alias_text": null,
"new_skill_meta": {
"derived": {
"category": "Concepts",
"skill_nature": "CONCEPT",
"sub_category": "general",
"typical_lifespan": "MULTI_YEAR",
"version_strategy": "UNVERSIONED",
"volatility": "MEDIUM"
},
"enrichment": null,
"keep_log": [],
"locked_dimensions": [],
"merge_log": [],
"placed": null,
"relationships": null,
"skill_id": "data-science",
"split_log": [],
"typed": null,
"warnings": []
},
"source_tag": "llm",
"was_in_llm_skills": true
},
{
"aliases_in_db": [
{
"alias_text": "DevOps",
"alias_type": "CANONICAL",
"id": 1852,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
}
],
"canonical": {
"category_id": 8,
"display_name": "DevOps",
"id": 1216,
"is_also_category": false,
"is_extractable": true,
"skill_nature": "METHODOLOGY",
"slug": "devops",
"sub_category_id": 922,
"typical_lifespan": "EVERGREEN",
"volatility": "STABLE"
},
"dimensions": [
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "CI/CD Pipeline Platforms",
"id": 150,
"rationale": "Systems used to define, run, and maintain automated build and deployment workflows. This cluster is coherent because the role owns delivery automation end to end, including pipeline reliability and promotion logic.",
"slug": "ci-cd-pipeline-platforms",
"source": "db"
},
"input_skill": "DevOps",
"llm_role": null,
"roles_from_db": [
{
"display_name": "DevOps Engineer",
"id": 10,
"rationale": null,
"role_archetype": null,
"slug": "devops-engineer",
"source": "db"
}
]
},
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Deployment and Release Patterns",
"id": 140,
"rationale": "Patterns for promoting changes safely across environments, including rollout, rollback, and release gating strategies. Cloud Architects define these patterns so teams can deploy consistently across the platform.",
"slug": "deployment-and-release-patterns",
"source": "db"
},
"input_skill": "DevOps",
"llm_role": null,
"roles_from_db": [
{
"display_name": "Cloud Architect",
"id": 9,
"rationale": null,
"role_archetype": null,
"slug": "cloud-architect",
"source": "db"
}
]
},
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Infrastructure as Code",
"id": 132,
"rationale": "Declarative provisioning and environment definition tools used to codify cloud infrastructure, repeatable environments, and platform standards. Cloud Architects use these to express reference architectures and guardrails.",
"slug": "infrastructure-as-code",
"source": "db"
},
"input_skill": "DevOps",
"llm_role": null,
"roles_from_db": [
{
"display_name": "Cloud Architect",
"id": 9,
"rationale": null,
"role_archetype": null,
"slug": "cloud-architect",
"source": "db"
},
{
"display_name": "DevOps Engineer",
"id": 10,
"rationale": null,
"role_archetype": null,
"slug": "devops-engineer",
"source": "db"
}
]
}
],
"input_skill": "DevOps",
"matched_via": "alias",
"new_alias_persisted": false,
"new_alias_text": null,
"new_skill_meta": null,
"source_tag": "db",
"was_in_llm_skills": true
}
],
"unmatched_skills": [
"HDFS",
"UNIX",
"Pig",
"ETL",
"Data Science"
]
}
API 3 — final-role-output
{
"chosen_role": {
"display_name": "Data Engineer",
"id": 2,
"rationale": "Exact alias hit on data-engineer (1.0) \u2014 no other alias at this confidence; skill_top data-engineer 0.50 does not contradict",
"role_archetype": null,
"slug": "data-engineer",
"source": "db"
},
"chosen_role_resolution": "in_db",
"final_input_skills": [
{
"skill": "Google Cloud Platform",
"tag": "in_db"
},
{
"skill": "Python",
"tag": "in_db"
},
{
"skill": "Java",
"tag": "in_db"
},
{
"skill": "PySpark",
"tag": "in_db"
},
{
"skill": "Spark",
"tag": "in_db"
},
{
"skill": "Scala",
"tag": "in_db"
},
{
"skill": "Hadoop",
"tag": "in_db"
},
{
"skill": "HDFS",
"tag": "new"
},
{
"skill": "Bash",
"tag": "in_db"
},
{
"skill": "UNIX",
"tag": "new"
},
{
"skill": "Hive",
"tag": "in_db"
},
{
"skill": "Cassandra",
"tag": "in_db"
},
{
"skill": "Pig",
"tag": "new"
},
{
"skill": "MySQL",
"tag": "in_db"
},
{
"skill": "NoSQL",
"tag": "in_db"
},
{
"skill": "ETL",
"tag": "new"
},
{
"skill": "Data Science",
"tag": "new"
},
{
"skill": "DevOps",
"tag": "in_db"
}
],
"llm_cost_api1_usd": null,
"llm_cost_api2_usd": null,
"llm_cost_api3_usd": null,
"llm_cost_total_usd": null,
"persistence": {
"items": [
{
"chosen_role_id": 2,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Cloud \u0026 Hosting Providers",
"id": 414,
"rationale": "Knowledge of major cloud and hosting vendor platforms for deploying and managing PHP applications.",
"slug": "cloud-hosting-providers",
"source": "db"
},
"dimension_id": 414,
"input_skill": "Google Cloud Platform",
"llm_role": null,
"matched_chosen_role": false,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
"role_dimension_saved": false,
"roles_from_db": [
{
"display_name": "PHP Backend Developer",
"id": 86,
"rationale": null,
"role_archetype": "Engineering",
"slug": "php-backend-developer",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 425,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 2,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Cloud Provider Platforms",
"id": 131,
"rationale": "Major cloud platforms and their core service ecosystems used to design target-state architectures, choose deployment boundaries, and evaluate managed capabilities. This is the primary substrate for cloud architecture decisions.",
"slug": "cloud-provider-platforms",
"source": "db"
},
"dimension_id": 131,
"input_skill": "Google Cloud Platform",
"llm_role": null,
"matched_chosen_role": false,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
"role_dimension_saved": false,
"roles_from_db": [
{
"display_name": "Cloud Architect",
"id": 9,
"rationale": null,
"role_archetype": null,
"slug": "cloud-architect",
"source": "db"
},
{
"display_name": "Cloud Security Engineer",
"id": 23,
"rationale": null,
"role_archetype": null,
"slug": "cloud-security-engineer",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 425,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 2,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Cloud Security Posture Tools",
"id": 64,
"rationale": "Cloud-native security platforms used to assess misconfiguration, workload exposure, and cloud control coverage. This dimension includes the major CNAPP/CSPM/CWPP vendors and cloud security services the role reviews and tunes.",
"slug": "cloud-security-posture-tools",
"source": "db"
},
"dimension_id": 64,
"input_skill": "Google Cloud Platform",
"llm_role": null,
"matched_chosen_role": false,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
"role_dimension_saved": false,
"roles_from_db": [
{
"display_name": "Cloud Security Engineer",
"id": 23,
"rationale": null,
"role_archetype": null,
"slug": "cloud-security-engineer",
"source": "db"
},
{
"display_name": "Cyber Security Engineer",
"id": 5,
"rationale": null,
"role_archetype": null,
"slug": "cybersecurity-engineer",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 425,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 2,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Cloud Security Scripting \u0026 DSL Languages",
"id": 248,
"rationale": "Proficiency in programming and domain-specific languages used to automate and script cloud security controls.",
"slug": "cloud-security-scripting-dsl-languages",
"source": "db"
},
"dimension_id": 248,
"input_skill": "Python",
"llm_role": null,
"matched_chosen_role": false,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
"role_dimension_saved": false,
"roles_from_db": [
{
"display_name": "Cloud Security Engineer",
"id": 23,
"rationale": null,
"role_archetype": null,
"slug": "cloud-security-engineer",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 5,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 2,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Programming Languages",
"id": 1,
"rationale": "Primary implementation languages used to build client and server feature code. Full stack engineers need enough fluency to move across layers and implement product behavior end to end.",
"slug": "programming-languages",
"source": "db"
},
"dimension_id": 1,
"input_skill": "Python",
"llm_role": null,
"matched_chosen_role": false,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
"role_dimension_saved": false,
"roles_from_db": [
{
"display_name": "Backend Developer",
"id": 1,
"rationale": null,
"role_archetype": "A Backend Engineer designs, builds, and maintains the server-side logic and data handling that power applications and services. They focus on implementing reliable business functionality, integrating with other systems, and ensuring the backend is scalable, maintainable, and observable.",
"slug": "backend-engineer",
"source": "db"
},
{
"display_name": "Fullstack Developer",
"id": 15,
"rationale": null,
"role_archetype": null,
"slug": "full-stack-engineer",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 5,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 2,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Programming Languages and Scripting",
"id": 59,
"rationale": "Languages used to write security automation, analysis scripts, detection logic, and remediation helpers. This is the primary implementation surface for a cybersecurity engineer across tooling and response workflows.",
"slug": "programming-languages-and-scripting",
"source": "db"
},
"dimension_id": 59,
"input_skill": "Python",
"llm_role": null,
"matched_chosen_role": false,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
"role_dimension_saved": false,
"roles_from_db": [
{
"display_name": "Cyber Security Engineer",
"id": 5,
"rationale": null,
"role_archetype": null,
"slug": "cybersecurity-engineer",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 5,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 2,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Programming Languages for Data Work",
"id": 21,
"rationale": "Languages used to implement data pipelines, transformations, and operational glue. This is the primary coding surface for building ingestion, enrichment, and automation logic in data engineering.",
"slug": "programming-languages-for-data-work",
"source": "db"
},
"dimension_id": 21,
"input_skill": "Python",
"llm_role": null,
"matched_chosen_role": true,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension saved",
"role_dimension_saved": true,
"roles_from_db": [
{
"display_name": "Data Engineer",
"id": 2,
"rationale": null,
"role_archetype": null,
"slug": "data-engineer",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 5,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 2,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Programming Languages for ML Systems",
"id": 39,
"rationale": "Languages used to build training code, inference services, evaluation jobs, and ML glue code. This is the primary implementation surface for ML engineers across experimentation and productionization.",
"slug": "programming-languages-for-ml-systems",
"source": "db"
},
"dimension_id": 39,
"input_skill": "Python",
"llm_role": null,
"matched_chosen_role": false,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
"role_dimension_saved": false,
"roles_from_db": [
{
"display_name": "ML Engineer",
"id": 3,
"rationale": null,
"role_archetype": null,
"slug": "ml-engineer",
"source": "db"
},
{
"display_name": "MLOps Engineer",
"id": 16,
"rationale": null,
"role_archetype": null,
"slug": "ml-ops-engineer",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 5,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 2,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Programming Languages for XR",
"id": 97,
"rationale": "Primary implementation languages used to build immersive client features, interaction logic, and device-specific runtime behavior. This is the core coding surface for AR/VR experiences.",
"slug": "programming-languages-for-xr",
"source": "db"
},
"dimension_id": 97,
"input_skill": "Python",
"llm_role": null,
"matched_chosen_role": false,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
"role_dimension_saved": false,
"roles_from_db": [
{
"display_name": "AR/VR Engineer",
"id": 8,
"rationale": null,
"role_archetype": null,
"slug": "ar-vr-engineer",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 5,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 2,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Python Programming",
"id": 290,
"rationale": "Core Python language skills used to implement backend business logic, request handlers, integrations, and service internals. This is the primary coding surface for the role.",
"slug": "python-programming",
"source": "db"
},
"dimension_id": 290,
"input_skill": "Python",
"llm_role": null,
"matched_chosen_role": false,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
"role_dimension_saved": false,
"roles_from_db": [
{
"display_name": "Python Backend Developer",
"id": 80,
"rationale": null,
"role_archetype": "Engineering",
"slug": "python-backend-developer",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 5,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 2,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Java Language and JVM",
"id": 279,
"rationale": "Core Java implementation skills used to build backend service logic, utilities, and internal abstractions. This is the primary coding surface for the role and includes language features plus JVM behavior that affect correctness and maintainability.",
"slug": "java-language-and-jvm",
"source": "db"
},
"dimension_id": 279,
"input_skill": "Java",
"llm_role": null,
"matched_chosen_role": false,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
"role_dimension_saved": false,
"roles_from_db": [
{
"display_name": "Java Backend Developer",
"id": 79,
"rationale": null,
"role_archetype": "Engineering",
"slug": "java-backend-developer",
"source": "db"
},
{
"display_name": "Kotlin Backend Developer",
"id": 84,
"rationale": null,
"role_archetype": "Engineering",
"slug": "kotlin-server-backend-developer",
"source": "db"
},
{
"display_name": "Scala Backend Developer",
"id": 87,
"rationale": null,
"role_archetype": "Engineering",
"slug": "scala-backend-developer",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 1,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 2,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Kotlin and Java",
"id": 161,
"rationale": "Primary implementation languages for Android app features, platform integration, and client-side business logic. Android engineers use these languages to build screens, state flows, service adapters, and device-aware behavior.",
"slug": "kotlin-and-java",
"source": "db"
},
"dimension_id": 161,
"input_skill": "Java",
"llm_role": null,
"matched_chosen_role": false,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
"role_dimension_saved": false,
"roles_from_db": [
{
"display_name": "Android Developer",
"id": 4,
"rationale": null,
"role_archetype": null,
"slug": "android-engineer",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 1,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 2,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Native Mobile Languages",
"id": 274,
"rationale": "Primary implementation languages used to build platform-specific app features, UI logic, and device integrations. This is the core coding surface for native mobile work on one platform.",
"slug": "native-mobile-languages",
"source": "db"
},
"dimension_id": 274,
"input_skill": "Java",
"llm_role": null,
"matched_chosen_role": false,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
"role_dimension_saved": false,
"roles_from_db": [
{
"display_name": "Native Mobile Developer",
"id": 75,
"rationale": null,
"role_archetype": "Engineering",
"slug": "native-mobile-developer",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 1,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 2,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Pega Programming Languages \u0026 DSLs",
"id": 267,
"rationale": "Programming languages and domain-specific languages used in Pega development.",
"slug": "pega-programming-languages-dsls",
"source": "db"
},
"dimension_id": 267,
"input_skill": "Java",
"llm_role": null,
"matched_chosen_role": false,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
"role_dimension_saved": false,
"roles_from_db": [
{
"display_name": "Pega Developer",
"id": 24,
"rationale": null,
"role_archetype": null,
"slug": "pega-developer",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 1,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 2,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Programming Languages",
"id": 1,
"rationale": "Primary implementation languages used to build client and server feature code. Full stack engineers need enough fluency to move across layers and implement product behavior end to end.",
"slug": "programming-languages",
"source": "db"
},
"dimension_id": 1,
"input_skill": "Java",
"llm_role": null,
"matched_chosen_role": false,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
"role_dimension_saved": false,
"roles_from_db": [
{
"display_name": "Backend Developer",
"id": 1,
"rationale": null,
"role_archetype": "A Backend Engineer designs, builds, and maintains the server-side logic and data handling that power applications and services. They focus on implementing reliable business functionality, integrating with other systems, and ensuring the backend is scalable, maintainable, and observable.",
"slug": "backend-engineer",
"source": "db"
},
{
"display_name": "Fullstack Developer",
"id": 15,
"rationale": null,
"role_archetype": null,
"slug": "full-stack-engineer",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 1,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 2,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Programming Languages for Data Work",
"id": 21,
"rationale": "Languages used to implement data pipelines, transformations, and operational glue. This is the primary coding surface for building ingestion, enrichment, and automation logic in data engineering.",
"slug": "programming-languages-for-data-work",
"source": "db"
},
"dimension_id": 21,
"input_skill": "Java",
"llm_role": null,
"matched_chosen_role": true,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension saved",
"role_dimension_saved": true,
"roles_from_db": [
{
"display_name": "Data Engineer",
"id": 2,
"rationale": null,
"role_archetype": null,
"slug": "data-engineer",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 1,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 2,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "ETL and ELT Tooling",
"id": 24,
"rationale": "Packaged tools for extracting, loading, and transforming data across systems. This dimension covers connector-based ingestion, transformation frameworks, and managed integration products.",
"slug": "etl-and-elt-tooling",
"source": "db"
},
"dimension_id": 24,
"input_skill": "PySpark",
"llm_role": null,
"matched_chosen_role": true,
"outcome_line": "Skipped \u2014 no persistable v3 meta for new skill",
"role_dimension_saved": false,
"roles_from_db": [
{
"display_name": "Data Engineer",
"id": 2,
"rationale": null,
"role_archetype": null,
"slug": "data-engineer",
"source": "db"
}
],
"skill_dimension_saved": false,
"skill_id": null,
"skill_tag": "new",
"skipped_reason": "skill_not_in_db_v3_proposed"
},
{
"chosen_role_id": 2,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "ETL and ELT Tooling",
"id": 24,
"rationale": "Packaged tools for extracting, loading, and transforming data across systems. This dimension covers connector-based ingestion, transformation frameworks, and managed integration products.",
"slug": "etl-and-elt-tooling",
"source": "db"
},
"dimension_id": 24,
"input_skill": "Spark",
"llm_role": null,
"matched_chosen_role": true,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension saved",
"role_dimension_saved": true,
"roles_from_db": [
{
"display_name": "Data Engineer",
"id": 2,
"rationale": null,
"role_archetype": null,
"slug": "data-engineer",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 1350,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 2,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Programming Languages for Data Work",
"id": 21,
"rationale": "Languages used to implement data pipelines, transformations, and operational glue. This is the primary coding surface for building ingestion, enrichment, and automation logic in data engineering.",
"slug": "programming-languages-for-data-work",
"source": "db"
},
"dimension_id": 21,
"input_skill": "Scala",
"llm_role": null,
"matched_chosen_role": true,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension saved",
"role_dimension_saved": true,
"roles_from_db": [
{
"display_name": "Data Engineer",
"id": 2,
"rationale": null,
"role_archetype": null,
"slug": "data-engineer",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 102,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 2,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Programming Languages for ML Systems",
"id": 39,
"rationale": "Languages used to build training code, inference services, evaluation jobs, and ML glue code. This is the primary implementation surface for ML engineers across experimentation and productionization.",
"slug": "programming-languages-for-ml-systems",
"source": "db"
},
"dimension_id": 39,
"input_skill": "Scala",
"llm_role": null,
"matched_chosen_role": false,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
"role_dimension_saved": false,
"roles_from_db": [
{
"display_name": "ML Engineer",
"id": 3,
"rationale": null,
"role_archetype": null,
"slug": "ml-engineer",
"source": "db"
},
{
"display_name": "MLOps Engineer",
"id": 16,
"rationale": null,
"role_archetype": null,
"slug": "ml-ops-engineer",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 102,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 2,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "ETL and ELT Tooling",
"id": 24,
"rationale": "Packaged tools for extracting, loading, and transforming data across systems. This dimension covers connector-based ingestion, transformation frameworks, and managed integration products.",
"slug": "etl-and-elt-tooling",
"source": "db"
},
"dimension_id": 24,
"input_skill": "Hadoop",
"llm_role": null,
"matched_chosen_role": true,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension saved",
"role_dimension_saved": true,
"roles_from_db": [
{
"display_name": "Data Engineer",
"id": 2,
"rationale": null,
"role_archetype": null,
"slug": "data-engineer",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 1351,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 2,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Programming Languages and Scripting",
"id": 59,
"rationale": "Languages used to write security automation, analysis scripts, detection logic, and remediation helpers. This is the primary implementation surface for a cybersecurity engineer across tooling and response workflows.",
"slug": "programming-languages-and-scripting",
"source": "db"
},
"dimension_id": 59,
"input_skill": "Bash",
"llm_role": null,
"matched_chosen_role": false,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
"role_dimension_saved": false,
"roles_from_db": [
{
"display_name": "Cyber Security Engineer",
"id": 5,
"rationale": null,
"role_archetype": null,
"slug": "cybersecurity-engineer",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 103,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 2,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Programming Languages for Data Work",
"id": 21,
"rationale": "Languages used to implement data pipelines, transformations, and operational glue. This is the primary coding surface for building ingestion, enrichment, and automation logic in data engineering.",
"slug": "programming-languages-for-data-work",
"source": "db"
},
"dimension_id": 21,
"input_skill": "Bash",
"llm_role": null,
"matched_chosen_role": true,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension saved",
"role_dimension_saved": true,
"roles_from_db": [
{
"display_name": "Data Engineer",
"id": 2,
"rationale": null,
"role_archetype": null,
"slug": "data-engineer",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 103,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 2,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Local Persistence and Offline Behavior",
"id": 85,
"rationale": "On-device storage used for caching, offline support, and durable client state. This cluster is coherent because iOS apps often need to preserve user progress and data when connectivity is limited.",
"slug": "local-persistence-and-offline-behavior",
"source": "db"
},
"dimension_id": 85,
"input_skill": "Hive",
"llm_role": null,
"matched_chosen_role": false,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
"role_dimension_saved": false,
"roles_from_db": [
{
"display_name": "Android Developer",
"id": 4,
"rationale": null,
"role_archetype": null,
"slug": "android-engineer",
"source": "db"
},
{
"display_name": "Flutter Developer",
"id": 74,
"rationale": null,
"role_archetype": "Engineering",
"slug": "flutter-developer",
"source": "db"
},
{
"display_name": "Hybrid Mobile Developer",
"id": 11,
"rationale": null,
"role_archetype": null,
"slug": "hybrid-mobile-developer",
"source": "db"
},
{
"display_name": "Native Mobile Developer",
"id": 75,
"rationale": null,
"role_archetype": "Engineering",
"slug": "native-mobile-developer",
"source": "db"
},
{
"display_name": "React Native Developer",
"id": 73,
"rationale": null,
"role_archetype": "Engineering",
"slug": "react-native-developer",
"source": "db"
},
{
"display_name": "iOS Developer",
"id": 6,
"rationale": null,
"role_archetype": null,
"slug": "ios-engineer",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 2754,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 2,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Cloud Storage and Data Services",
"id": 144,
"rationale": "Cloud-native storage and managed data services used to place workloads, choose durability tiers, and define platform boundaries. This is a coherent cluster because architects evaluate storage fit, access patterns, and managed service tradeoffs.",
"slug": "cloud-storage-and-data-services",
"source": "db"
},
"dimension_id": 144,
"input_skill": "Cassandra",
"llm_role": null,
"matched_chosen_role": false,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
"role_dimension_saved": false,
"roles_from_db": [
{
"display_name": "Cloud Architect",
"id": 9,
"rationale": null,
"role_archetype": null,
"slug": "cloud-architect",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 1354,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 2,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Relational Data Modeling",
"id": 216,
"rationale": "Modeling and tuning relational persistence for backend features. PHP backend developers need this to shape schemas, indexes, transactions, and query-aware data structures that support application behavior.",
"slug": "relational-data-modeling",
"source": "db"
},
"dimension_id": 216,
"input_skill": "MySQL",
"llm_role": null,
"matched_chosen_role": false,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
"role_dimension_saved": false,
"roles_from_db": [
{
"display_name": "Fullstack Developer",
"id": 15,
"rationale": null,
"role_archetype": null,
"slug": "full-stack-engineer",
"source": "db"
},
{
"display_name": "PHP Backend Developer",
"id": 86,
"rationale": null,
"role_archetype": "Engineering",
"slug": "php-backend-developer",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 17,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 2,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Relational Database Design",
"id": 4,
"rationale": "Modeling and operating relational persistence for backend services. Includes schema design, normalization, indexing, transactions, and query tuning for operational data stores.",
"slug": "relational-database-design",
"source": "db"
},
"dimension_id": 4,
"input_skill": "MySQL",
"llm_role": null,
"matched_chosen_role": false,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
"role_dimension_saved": false,
"roles_from_db": [
{
"display_name": ".NET Backend Developer",
"id": 83,
"rationale": null,
"role_archetype": "Engineering",
"slug": "dotnet-backend-developer",
"source": "db"
},
{
"display_name": "Backend Developer",
"id": 1,
"rationale": null,
"role_archetype": "A Backend Engineer designs, builds, and maintains the server-side logic and data handling that power applications and services. They focus on implementing reliable business functionality, integrating with other systems, and ensuring the backend is scalable, maintainable, and observable.",
"slug": "backend-engineer",
"source": "db"
},
{
"display_name": "Kotlin Backend Developer",
"id": 84,
"rationale": null,
"role_archetype": "Engineering",
"slug": "kotlin-server-backend-developer",
"source": "db"
},
{
"display_name": "Node.js Backend Developer",
"id": 82,
"rationale": null,
"role_archetype": "Engineering",
"slug": "node-backend-developer",
"source": "db"
},
{
"display_name": "Python Backend Developer",
"id": 80,
"rationale": null,
"role_archetype": "Engineering",
"slug": "python-backend-developer",
"source": "db"
},
{
"display_name": "Ruby Backend Developer",
"id": 85,
"rationale": null,
"role_archetype": "Engineering",
"slug": "ruby-backend-developer",
"source": "db"
},
{
"display_name": "Scala Backend Developer",
"id": 87,
"rationale": null,
"role_archetype": "Engineering",
"slug": "scala-backend-developer",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 17,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 2,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Relational Database Usage",
"id": 371,
"rationale": "Working effectively with operational relational databases from Go backend services. This includes schema-aware querying, indexing awareness, transactions, and understanding how service code interacts with PostgreSQL or similar systems.",
"slug": "relational-database-usage",
"source": "db"
},
"dimension_id": 371,
"input_skill": "MySQL",
"llm_role": null,
"matched_chosen_role": false,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
"role_dimension_saved": false,
"roles_from_db": [
{
"display_name": "Go Backend Developer",
"id": 81,
"rationale": null,
"role_archetype": "Engineering",
"slug": "go-backend-developer",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 17,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 2,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "NoSQL Databases",
"id": 19,
"rationale": "Models and manages data using non-relational database systems.",
"slug": "nosql-databases",
"source": "db"
},
"dimension_id": 19,
"input_skill": "NoSQL",
"llm_role": null,
"matched_chosen_role": false,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
"role_dimension_saved": false,
"roles_from_db": [
{
"display_name": "Backend Developer",
"id": 1,
"rationale": null,
"role_archetype": "A Backend Engineer designs, builds, and maintains the server-side logic and data handling that power applications and services. They focus on implementing reliable business functionality, integrating with other systems, and ensuring the backend is scalable, maintainable, and observable.",
"slug": "backend-engineer",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 1346,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 2,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "CI/CD Pipeline Platforms",
"id": 150,
"rationale": "Systems used to define, run, and maintain automated build and deployment workflows. This cluster is coherent because the role owns delivery automation end to end, including pipeline reliability and promotion logic.",
"slug": "ci-cd-pipeline-platforms",
"source": "db"
},
"dimension_id": 150,
"input_skill": "DevOps",
"llm_role": null,
"matched_chosen_role": false,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
"role_dimension_saved": false,
"roles_from_db": [
{
"display_name": "DevOps Engineer",
"id": 10,
"rationale": null,
"role_archetype": null,
"slug": "devops-engineer",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 1216,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 2,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Deployment and Release Patterns",
"id": 140,
"rationale": "Patterns for promoting changes safely across environments, including rollout, rollback, and release gating strategies. Cloud Architects define these patterns so teams can deploy consistently across the platform.",
"slug": "deployment-and-release-patterns",
"source": "db"
},
"dimension_id": 140,
"input_skill": "DevOps",
"llm_role": null,
"matched_chosen_role": false,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
"role_dimension_saved": false,
"roles_from_db": [
{
"display_name": "Cloud Architect",
"id": 9,
"rationale": null,
"role_archetype": null,
"slug": "cloud-architect",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 1216,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 2,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Infrastructure as Code",
"id": 132,
"rationale": "Declarative provisioning and environment definition tools used to codify cloud infrastructure, repeatable environments, and platform standards. Cloud Architects use these to express reference architectures and guardrails.",
"slug": "infrastructure-as-code",
"source": "db"
},
"dimension_id": 132,
"input_skill": "DevOps",
"llm_role": null,
"matched_chosen_role": false,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
"role_dimension_saved": false,
"roles_from_db": [
{
"display_name": "Cloud Architect",
"id": 9,
"rationale": null,
"role_archetype": null,
"slug": "cloud-architect",
"source": "db"
},
{
"display_name": "DevOps Engineer",
"id": 10,
"rationale": null,
"role_archetype": null,
"slug": "devops-engineer",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 1216,
"skill_tag": "in_db",
"skipped_reason": null
}
],
"new_skills_created": 0,
"role_dimension_saved": 0,
"skill_dimension_saved": 0,
"skipped": 1
},
"planner_output": null,
"run_id": "9eb27c7e-c22e-4e2c-8c17-6c24aff1efe1"
}
LLM Calls
Every model call made for this run, in pipeline order. Click a card to see the model's response.