Pipeline run
6de4c471-b63e-4025-bbf8-0049eb5c1771
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 0.22 does not contradict
Resolution:
in_db
— role exists in library; skill↔dim and role↔dim links saved when applicable.
Job description
Project Description We've been engaged by a large Australian financial institution to provide resources to their FRTB Market Risk project. Joining this program you will have the benefit of working with an established client team, fully involved in the project initiation through to project implementation. The role will focus on building out the Palantir setup related to new requirements around Capital Markets (Market Risk, Credit Risk etc). Responsibilities You will be a Data Engineer with ETL, Python and ideally PySpark experience. The work will focus on implementing Palantir Foundry logic based on existing Palantir patterns and leveraging Python, PySpark. Skills Must have Data ETL: Data ingestion, Data pipelines, Data Quality and Lineage, Experienced in Python development and deployment. Able to demonstrate knowledge and practical application of best practices. Knowledge of Spark. Ideally experience writing PySpark, but experience with Scala Spark or even Spark SQL would also be considered Palantir Foundry (desirable) Able to demonstrate an understanding of the principles and application of data science and the practical application through the application of statistical models Exception management when handling data Understanding of data health checks Ability to work within described patterns Nice to have Exposure to Capital Markets: FX, IRD, MM, Equity etc is highly regarded Some experience in Java Web experience (Javascript/HTML/CSS/Handlebars.js) Machine learning - knowledge of basic machine learning techniques Understanding of Market Risk within Capital Markets Languages English: C1 Advanced
Skills from this JD
Each row merges API 1 extraction, API 2 library match / v3 orchestration (dimensions + locked dims), and API 3 persistence tags.
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
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, Fullstack Developer
-
Programming Languages & DSLs Catalog dimension db id 475
Library dimension (catalog)
Roles linked in library: Engineering Manager
-
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 & DSLs
programming-languages-dsls
|
✓ | — | 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
- 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
|
Skill enrichment (orchestrator / LLM)
No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).
- Category
- Platforms
- Sub-category
- general
- Skill nature
- PLATFORM
- 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
- 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
- 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
- Data Engineering Tools
- Sub-category
- general
- Skill nature
- CONCEPT
- 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
- Data Engineering Tools
- Sub-category
- general
- Skill nature
- CONCEPT
- Volatility
- MEDIUM
- Typical lifespan
- MULTI_YEAR
- Version strategy
- UNVERSIONED
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) |
Skill enrichment (orchestrator / LLM)
No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).
- Category
- Programming Languages
- Sub-category
- general
- Skill nature
- LANGUAGE
- 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
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
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, Fullstack Developer
-
Programming Languages & DSLs Catalog dimension db id 475
Library dimension (catalog)
Roles linked in library: Engineering Manager
-
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 & DSLs
programming-languages-dsls
|
✓ | — | 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
- JavaScript (CANONICAL) primary
- ES2015 (VERSION)
- ES2016 (VERSION)
- ES2017 (VERSION)
- ES2018 (VERSION)
- ES2019 (VERSION)
- ES2020 (VERSION)
- ES2021 (VERSION)
- ES2022 (VERSION)
- ES2023 (VERSION)
- ES2024 (VERSION)
- ES5 (VERSION)
- ES6 (VERSION)
- JavaScript ES2015 (VERSION)
- JavaScript ES2020 (VERSION)
- JavaScript ES6 (VERSION)
- modern JavaScript (VERSION)
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Language
- Sub-category
- Programming Language
- Vendor
- Mozilla
- License
- mpl
- Year introduced
- 1995
- Confidence
- 0.99
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: JavaScript appears in a very high volume of job postings across frontend, backend, and full-stack roles, and remains a core language in major ecosystems like Node.js and React.
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)
-
Cross-Platform App Languages Catalog dimension db id 167
Library dimension (catalog)
Roles linked in library: Hybrid Mobile Developer
-
JavaScript and TypeScript Catalog dimension db id 114
Library dimension (catalog)
Roles linked in library: Angular Frontend Developer, Frontend Developer, Ionic Developer, Node.js Backend Developer, React Frontend Developer, React Native Developer, Svelte Frontend Developer, Vue Frontend Developer, Web Developer
-
JavaScript for WordPress Catalog dimension db id 329
Library dimension (catalog)
Roles linked in library: WordPress Dev
-
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, Fullstack Developer
-
Programming Languages & DSLs Catalog dimension db id 475
Library dimension (catalog)
Roles linked in library: Engineering Manager
-
Programming Languages & Template Languages Catalog dimension db id 359
Library dimension (catalog)
Roles linked in library: Drupal Dev
-
Sitecore Development Languages Catalog dimension db id 438
Library dimension (catalog)
Roles linked in library: Sitecore Dev
-
Storefront JavaScript and DOM Behavior Catalog dimension db id 422
Library dimension (catalog)
Roles linked in library: Shopify Dev
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
Cross-Platform App Languages
cross-platform-app-languages
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
JavaScript and TypeScript
javascript-and-typescript
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
JavaScript for WordPress
javascript-for-wordpress
|
✓ | — | 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 & DSLs
programming-languages-dsls
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Programming Languages & Template Languages
programming-languages-template-languages
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Sitecore Development Languages
sitecore-development-languages
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Storefront JavaScript and DOM Behavior
storefront-javascript-and-dom-behavior
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
Aliases — catalog
- HTML (CANONICAL) primary
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Language
- Sub-category
- Markup Language
- Vendor
- W3C
- License
- unknown
- Year introduced
- 1993
- Confidence
- 0.99
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: HTML appears in the vast majority of web/front-end job descriptions and remains a core browser standard; it is not sunset or replaced by a newer markup language.
Skill profile (library / DB)
- Skill nature
- LANGUAGE
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 6
- Sub-category id
- 1467
- Extractable
- True
- Also category
- False
Dimensions (API 2 worklist)
-
Pega Programming Languages & DSLs Catalog dimension db id 267
Library dimension (catalog)
Roles linked in library: Pega Developer
-
Programming Languages & Template Languages Catalog dimension db id 359
Library dimension (catalog)
Roles linked in library: Drupal Dev
-
React Frontend Development Catalog dimension db id 96
Library dimension (catalog)
-
Sitecore Development Languages Catalog dimension db id 438
Library dimension (catalog)
Roles linked in library: Sitecore Dev
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
Pega Programming Languages & DSLs
pega-programming-languages-dsls
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Programming Languages & Template Languages
programming-languages-template-languages
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
React Frontend Development
d_init_01
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Sitecore Development Languages
sitecore-development-languages
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
Aliases — catalog
- CSS (CANONICAL) primary
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Language
- Sub-category
- Stylesheet Language
- Vendor
- W3C
- License
- unknown
- Year introduced
- 1996
- Confidence
- 0.99
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: CSS is a core front-end skill in most web JDs and remains standard in MDN/browser docs; it’s broadly used alongside HTML/JS rather than being replaced by a successor.
Skill profile (library / DB)
- Skill nature
- LANGUAGE
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 6
- Sub-category id
- 486
- Extractable
- True
- Also category
- False
Dimensions (API 2 worklist)
-
CSS Architecture and Styling Catalog dimension db id 117
Library dimension (catalog)
Roles linked in library: Frontend Developer, Fullstack Developer, Fullstack Developer, React Frontend Developer, Svelte Frontend Developer, Vue Frontend Developer, Web Developer
-
Programming Languages & Template Languages Catalog dimension db id 359
Library dimension (catalog)
Roles linked in library: Drupal Dev
-
Sitecore Development Languages Catalog dimension db id 438
Library dimension (catalog)
Roles linked in library: Sitecore Dev
-
Storefront Styling and Responsive Layout Catalog dimension db id 423
Library dimension (catalog)
Roles linked in library: Shopify Dev
-
Styling and Responsive Layout Catalog dimension db id 307
Library dimension (catalog)
Roles linked in library: Angular Frontend Developer
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
CSS Architecture and Styling
css-architecture-and-styling
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Programming Languages & Template Languages
programming-languages-template-languages
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Sitecore Development Languages
sitecore-development-languages
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Storefront Styling and Responsive Layout
storefront-styling-and-responsive-layout
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Styling and Responsive Layout
styling-and-responsive-layout
|
✓ | — | 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
- Web Frameworks
- Sub-category
- general
- Skill nature
- TOOL
- Volatility
- MEDIUM
- Typical lifespan
- MULTI_YEAR
- Version strategy
- UNVERSIONED
Aliases — catalog
- Machine Learning (CANONICAL)
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Concept
- Sub-category
- Machine Learning
- Confidence
- 0.98
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: Machine Learning appears in large volumes of job descriptions across data, product, and platform roles, and major cloud vendors (AWS, Google Cloud, Azure) offer dedicated ML services and certifications, indicating broad adoption.
Skill profile (library / DB)
- Skill nature
- CONCEPT
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 2
- Sub-category id
- 1024
- Extractable
- True
- Also category
- False
Dimensions (API 2 worklist)
-
AI Governance and Model Security Catalog dimension db id 50
Library dimension (catalog)
Roles linked in library: AI Engineer, ML Engineer, MLOps Engineer
-
React Frontend Development Catalog dimension db id 96
Library dimension (catalog)
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
AI Governance and Model Security
ai-governance-and-model-security
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
React Frontend Development
d_init_01
|
✓ | — | 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 |
|---|---|---|---|---|---|---|
| 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 & DSLs
programming-languages-dsls
|
✓ | — | 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) | |
| 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) | |
| 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 & DSLs
programming-languages-dsls
|
✓ | — | 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 | |
| JavaScript | in_db |
Cross-Platform App Languages
cross-platform-app-languages
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| JavaScript | in_db |
JavaScript and TypeScript
javascript-and-typescript
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| JavaScript | in_db |
JavaScript for WordPress
javascript-for-wordpress
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| JavaScript | in_db |
Pega Programming Languages & DSLs
pega-programming-languages-dsls
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| JavaScript | in_db |
Programming Languages
programming-languages
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| JavaScript | in_db |
Programming Languages & DSLs
programming-languages-dsls
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| JavaScript | in_db |
Programming Languages & Template Languages
programming-languages-template-languages
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| JavaScript | in_db |
Sitecore Development Languages
sitecore-development-languages
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| JavaScript | in_db |
Storefront JavaScript and DOM Behavior
storefront-javascript-and-dom-behavior
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| HTML | in_db |
Pega Programming Languages & DSLs
pega-programming-languages-dsls
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| HTML | in_db |
Programming Languages & Template Languages
programming-languages-template-languages
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| HTML | in_db |
React Frontend Development
d_init_01
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| HTML | in_db |
Sitecore Development Languages
sitecore-development-languages
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| CSS | in_db |
CSS Architecture and Styling
css-architecture-and-styling
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| CSS | in_db |
Programming Languages & Template Languages
programming-languages-template-languages
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| CSS | in_db |
Sitecore Development Languages
sitecore-development-languages
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| CSS | in_db |
Storefront Styling and Responsive Layout
storefront-styling-and-responsive-layout
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| CSS | in_db |
Styling and Responsive Layout
styling-and-responsive-layout
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Machine Learning | in_db |
AI Governance and Model Security
ai-governance-and-model-security
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Machine Learning | in_db |
React Frontend Development
d_init_01
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
Library artifacts (this run)
| Kind | Detail | DB id |
|---|---|---|
| canonical_skill_proposed | ETL | type=Data Engineering Tools subtype=general nature=PRACTICE lifespan=MULTI_YEAR | |
| canonical_skill_proposed | Palantir Foundry | type=Platforms subtype=general nature=PLATFORM lifespan=MULTI_YEAR | |
| canonical_skill_proposed | Data Ingestion | type=Data Engineering Tools subtype=general nature=PRACTICE lifespan=MULTI_YEAR | |
| canonical_skill_proposed | Data Pipelines | type=Data Engineering Tools subtype=general nature=PRACTICE lifespan=MULTI_YEAR | |
| canonical_skill_proposed | Data Quality | type=Data Engineering Tools subtype=general nature=CONCEPT lifespan=MULTI_YEAR | |
| canonical_skill_proposed | Data Lineage | type=Data Engineering Tools subtype=general nature=CONCEPT lifespan=MULTI_YEAR | |
| canonical_skill_proposed | Spark SQL | type=Programming Languages subtype=general nature=LANGUAGE lifespan=MULTI_YEAR | |
| canonical_skill_proposed | Statistical Models | type=Concepts subtype=general nature=CONCEPT lifespan=MULTI_YEAR | |
| canonical_skill_proposed | Data Health Checks | type=Data Engineering Tools subtype=general nature=PRACTICE lifespan=MULTI_YEAR | |
| canonical_skill_proposed | Handlebars.js | type=Web Frameworks subtype=general nature=TOOL 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": [
"FinTech",
"Banking"
],
"domain": "Financial Services"
},
"secondary": null
},
"education": [],
"experience": null,
"job_locations": [],
"role": "Data Engineer",
"role_aliases": [
"Data Engineer",
"ETL Engineer",
"Data Developer"
],
"role_archetype": "Data",
"roles_and_responsibilities": [
{
"bullet_count": 0,
"heading": "Responsibilities",
"heading_was_present": true,
"source_marker": {
"first_5_words": "You will be a Data",
"last_5_words": "and leveraging Python, PySpark."
},
"text": "You will be a Data Engineer with ETL, Python and ideally PySpark experience.\n\nThe work will focus on implementing Palantir Foundry logic based on existing Palantir patterns and leveraging Python, PySpark.",
"word_count": 36
},
{
"bullet_count": 0,
"heading": "Skills",
"heading_was_present": true,
"source_marker": {
"first_5_words": "Must have Data ETL: Data",
"last_5_words": "within Capital Markets"
},
"text": "Must have\n Data ETL: Data ingestion, Data pipelines, Data Quality and Lineage, Experienced in Python development and deployment. Able to demonstrate knowledge and practical application of best practices. Knowledge of Spark. Ideally experience writing PySpark, but experience with Scala Spark or even Spark SQL would also be considered Palantir Foundry (desirable) Able to demonstrate an understanding of the principles and application of data science and the practical application through the application of statistical models Exception management when handling data Understanding of data health checks Ability to work within described patterns\nNice to have\n Exposure to Capital Markets: FX, IRD, MM, Equity etc is highly regarded Some experience in Java Web experience (Javascript/HTML/CSS/Handlebars.js) Machine learning - knowledge of basic machine learning techniques Understanding of Market Risk within Capital Markets",
"word_count": 246
}
],
"urls": []
}
API 1 — extract-from-jd click to toggle
{
"final_skills": [
{
"is_primary": true,
"skill_name": "ETL"
},
{
"is_primary": true,
"skill_name": "Python"
},
{
"is_primary": true,
"skill_name": "PySpark"
},
{
"is_primary": false,
"skill_name": "Palantir Foundry"
},
{
"is_primary": true,
"skill_name": "Data Ingestion"
},
{
"is_primary": true,
"skill_name": "Data Pipelines"
},
{
"is_primary": true,
"skill_name": "Data Quality"
},
{
"is_primary": true,
"skill_name": "Data Lineage"
},
{
"is_primary": true,
"skill_name": "Spark"
},
{
"is_primary": false,
"skill_name": "Scala"
},
{
"is_primary": false,
"skill_name": "Spark SQL"
},
{
"is_primary": false,
"skill_name": "Statistical Models"
},
{
"is_primary": true,
"skill_name": "Data Health Checks"
},
{
"is_primary": false,
"skill_name": "Java"
},
{
"is_primary": false,
"skill_name": "JavaScript"
},
{
"is_primary": false,
"skill_name": "HTML"
},
{
"is_primary": false,
"skill_name": "CSS"
},
{
"is_primary": false,
"skill_name": "Handlebars.js"
},
{
"is_primary": false,
"skill_name": "Machine Learning"
}
],
"jd_role": {
"display_name": "Data Engineer",
"rationale": null,
"role_aliases": [
"Data Engineer",
"ETL Engineer",
"Data Developer"
],
"role_archetype": "Data",
"slug": ""
},
"nano_parsed": {
"JD_type": "pass",
"about_company": null,
"certifications": [],
"company_name": "null",
"ctc": null,
"domain": {
"primary": {
"aliases": [
"FinTech",
"Banking"
],
"domain": "Financial Services"
},
"secondary": null
},
"education": [],
"experience": null,
"job_locations": [],
"role": "Data Engineer",
"role_aliases": [
"Data Engineer",
"ETL Engineer",
"Data Developer"
],
"role_archetype": "Data",
"roles_and_responsibilities": [
{
"bullet_count": 0,
"heading": "Responsibilities",
"heading_was_present": true,
"source_marker": {
"first_5_words": "You will be a Data",
"last_5_words": "and leveraging Python, PySpark."
},
"text": "You will be a Data Engineer with ETL, Python and ideally PySpark experience.\n\nThe work will focus on implementing Palantir Foundry logic based on existing Palantir patterns and leveraging Python, PySpark.",
"word_count": 36
},
{
"bullet_count": 0,
"heading": "Skills",
"heading_was_present": true,
"source_marker": {
"first_5_words": "Must have Data ETL: Data",
"last_5_words": "within Capital Markets"
},
"text": "Must have\n Data ETL: Data ingestion, Data pipelines, Data Quality and Lineage, Experienced in Python development and deployment. Able to demonstrate knowledge and practical application of best practices. Knowledge of Spark. Ideally experience writing PySpark, but experience with Scala Spark or even Spark SQL would also be considered Palantir Foundry (desirable) Able to demonstrate an understanding of the principles and application of data science and the practical application through the application of statistical models Exception management when handling data Understanding of data health checks Ability to work within described patterns\nNice to have\n Exposure to Capital Markets: FX, IRD, MM, Equity etc is highly regarded Some experience in Java Web experience (Javascript/HTML/CSS/Handlebars.js) Machine learning - knowledge of basic machine learning techniques Understanding of Market Risk within Capital Markets",
"word_count": 246
}
],
"urls": []
},
"rejected": false,
"rejection_reason": null,
"run_id": "6de4c471-b63e-4025-bbf8-0049eb5c1771",
"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": "Works with data analysts, data scientists, and business stakeholders to define data models, ingestion schedules, and data delivery requirements.",
"sentence": "Data ETL: Data ingestion, Data pipelines, Data Quality and Lineage, Experienced in Python development and deployment.",
"similarity": 0.5778
},
{
"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": "Ideally experience writing PySpark, but experience with Scala Spark or even Spark SQL would also be considered Palantir Foundry (desirable) Able to demonstrate an understanding of the principles and application of data science and the practical application through the application of statistical models Exception management when handling data Understanding of data health checks Ability to work within described patterns",
"similarity": 0.514
},
{
"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": "You will be a Data Engineer with ETL, Python and ideally PySpark experience.",
"similarity": 0.4921
}
],
"matched_count": null,
"matched_skills": null,
"role_id": 2,
"score": 0.528,
"slug": "data-engineer",
"total_count": null
},
{
"display_name": "AI Engineer",
"kra_matches": [
{
"kra_text": "Designs and implements prompt engineering workflows, few-shot examples, chain-of-thought patterns, and structured output parsing for AI feature pipelines.",
"sentence": "The work will focus on implementing Palantir Foundry logic based on existing Palantir patterns and leveraging Python, PySpark.",
"similarity": 0.4924
},
{
"kra_text": "Designs and implements prompt engineering workflows, few-shot examples, chain-of-thought patterns, and structured output parsing for AI feature pipelines.",
"sentence": "Data ETL: Data ingestion, Data pipelines, Data Quality and Lineage, Experienced in Python development and deployment.",
"similarity": 0.4299
},
{
"kra_text": "Designs and implements prompt engineering workflows, few-shot examples, chain-of-thought patterns, and structured output parsing for AI feature pipelines.",
"sentence": "Ideally experience writing PySpark, but experience with Scala Spark or even Spark SQL would also be considered Palantir Foundry (desirable) Able to demonstrate an understanding of the principles and application of data science and the practical application through the application of statistical models Exception management when handling data Understanding of data health checks Ability to work within described patterns",
"similarity": 0.4278
}
],
"matched_count": null,
"matched_skills": null,
"role_id": 13,
"score": 0.45,
"slug": "ai-engineer",
"total_count": null
},
{
"display_name": "ML Engineer",
"kra_matches": [
{
"kra_text": "Prepares, cleans, and transforms training datasets, manages feature stores, and builds feature engineering pipelines for model training.",
"sentence": "Data ETL: Data ingestion, Data pipelines, Data Quality and Lineage, Experienced in Python development and deployment.",
"similarity": 0.4801
},
{
"kra_text": "Prepares, cleans, and transforms training datasets, manages feature stores, and builds feature engineering pipelines for model training.",
"sentence": "You will be a Data Engineer with ETL, Python and ideally PySpark experience.",
"similarity": 0.4278
},
{
"kra_text": "Designs end-to-end ML training pipelines and model inference workflows using TensorFlow, PyTorch, or scikit-learn on cloud ML platforms.",
"sentence": "The work will focus on implementing Palantir Foundry logic based on existing Palantir patterns and leveraging Python, PySpark.",
"similarity": 0.4139
}
],
"matched_count": null,
"matched_skills": null,
"role_id": 3,
"score": 0.4406,
"slug": "ml-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": "The work will focus on implementing Palantir Foundry logic based on existing Palantir patterns and leveraging Python, PySpark.",
"similarity": 0.403
},
{
"kra_text": "Designs and queries relational databases like PostgreSQL and document stores like MongoDB, writing migrations, indexes, and optimized queries.",
"sentence": "Ideally experience writing PySpark, but experience with Scala Spark or even Spark SQL would also be considered Palantir Foundry (desirable) Able to demonstrate an understanding of the principles and application of data science and the practical application through the application of statistical models Exception management when handling data Understanding of data health checks Ability to work within described patterns",
"similarity": 0.3949
},
{
"kra_text": "Designs and queries relational databases like PostgreSQL and document stores like MongoDB, writing migrations, indexes, and optimized queries.",
"sentence": "Data ETL: Data ingestion, Data pipelines, Data Quality and Lineage, Experienced in Python development and deployment.",
"similarity": 0.3889
}
],
"matched_count": null,
"matched_skills": null,
"role_id": 15,
"score": 0.3956,
"slug": "full-stack-engineer",
"total_count": null
},
{
"display_name": "MLOps Engineer",
"kra_matches": [
{
"kra_text": "Automates ML platform operations including scheduled retraining triggers, pipeline orchestration, evaluation workflows, and alerting configuration.",
"sentence": "Data ETL: Data ingestion, Data pipelines, Data Quality and Lineage, Experienced in Python development and deployment.",
"similarity": 0.3974
},
{
"kra_text": "Supports ML platform incidents by diagnosing model serving failures, feature store pipeline breaks, and training environment configuration issues.",
"sentence": "Ideally experience writing PySpark, but experience with Scala Spark or even Spark SQL would also be considered Palantir Foundry (desirable) Able to demonstrate an understanding of the principles and application of data science and the practical application through the application of statistical models Exception management when handling data Understanding of data health checks Ability to work within described patterns",
"similarity": 0.3812
},
{
"kra_text": "Automates ML platform operations including scheduled retraining triggers, pipeline orchestration, evaluation workflows, and alerting configuration.",
"sentence": "The work will focus on implementing Palantir Foundry logic based on existing Palantir patterns and leveraging Python, PySpark.",
"similarity": 0.3569
}
],
"matched_count": null,
"matched_skills": null,
"role_id": 16,
"score": 0.3785,
"slug": "ml-ops-engineer",
"total_count": null
}
],
"skill_match_roles": [
{
"display_name": "Data Engineer",
"kra_matches": null,
"matched_count": 2,
"matched_skills": [
"Apache Spark",
"Python"
],
"role_id": 2,
"score": 0.2222,
"slug": "data-engineer",
"total_count": 9
},
{
"display_name": "ML Engineer",
"kra_matches": null,
"matched_count": 1,
"matched_skills": [
"Python"
],
"role_id": 3,
"score": 0.1111,
"slug": "ml-engineer",
"total_count": 9
},
{
"display_name": "Cyber Security Engineer",
"kra_matches": null,
"matched_count": 1,
"matched_skills": [
"Python"
],
"role_id": 5,
"score": 0.1111,
"slug": "cybersecurity-engineer",
"total_count": 9
},
{
"display_name": "AR/VR Engineer",
"kra_matches": null,
"matched_count": 1,
"matched_skills": [
"Python"
],
"role_id": 8,
"score": 0.1111,
"slug": "ar-vr-engineer",
"total_count": 9
},
{
"display_name": "Backend Developer",
"kra_matches": null,
"matched_count": 1,
"matched_skills": [
"Python"
],
"role_id": 1,
"score": 0.1111,
"slug": "backend-engineer",
"total_count": 9
}
]
},
"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 0.22 does not contradict",
"sub_role": null
},
"stage5_updates": {
"centroid_n_after": 283,
"centroid_updated": true,
"collision_log_id": null,
"new_kra_attached": null,
"new_skills_attached": [
{
"is_primary": true,
"queue_id": 13849,
"role_display_name": "Data Engineer",
"role_slug": "data-engineer",
"skill_name": "ETL",
"status": "pending"
},
{
"is_primary": true,
"queue_id": 13850,
"role_display_name": "Data Engineer",
"role_slug": "data-engineer",
"skill_name": "PySpark",
"status": "pending"
},
{
"is_primary": false,
"queue_id": 13851,
"role_display_name": "Data Engineer",
"role_slug": "data-engineer",
"skill_name": "Palantir Foundry",
"status": "pending"
},
{
"is_primary": true,
"queue_id": 13852,
"role_display_name": "Data Engineer",
"role_slug": "data-engineer",
"skill_name": "Data Ingestion",
"status": "pending"
},
{
"is_primary": true,
"queue_id": 13853,
"role_display_name": "Data Engineer",
"role_slug": "data-engineer",
"skill_name": "Data Pipelines",
"status": "pending"
},
{
"is_primary": true,
"queue_id": 13854,
"role_display_name": "Data Engineer",
"role_slug": "data-engineer",
"skill_name": "Data Quality",
"status": "pending"
},
{
"is_primary": true,
"queue_id": 13855,
"role_display_name": "Data Engineer",
"role_slug": "data-engineer",
"skill_name": "Data Lineage",
"status": "pending"
},
{
"is_primary": false,
"queue_id": 13856,
"role_display_name": "Data Engineer",
"role_slug": "data-engineer",
"skill_name": "Spark SQL",
"status": "pending"
},
{
"is_primary": false,
"queue_id": 13857,
"role_display_name": "Data Engineer",
"role_slug": "data-engineer",
"skill_name": "Statistical Models",
"status": "pending"
},
{
"is_primary": true,
"queue_id": 13858,
"role_display_name": "Data Engineer",
"role_slug": "data-engineer",
"skill_name": "Data Health Checks",
"status": "pending"
},
{
"is_primary": false,
"queue_id": 13859,
"role_display_name": "Data Engineer",
"role_slug": "data-engineer",
"skill_name": "Handlebars.js",
"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": 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": "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": 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": "alias_text already exists for this canonical skill",
"alias_persisted": false,
"existing_alias_id": 1028,
"existing_alias_text": "JavaScript",
"input_term": "JavaScript",
"matched_canonical": {
"category_id": 6,
"display_name": "JavaScript",
"id": 607,
"is_also_category": false,
"is_extractable": true,
"skill_nature": "LANGUAGE",
"slug": "javascript",
"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": 2627,
"existing_alias_text": "HTML",
"input_term": "HTML",
"matched_canonical": {
"category_id": 6,
"display_name": "HTML",
"id": 1657,
"is_also_category": false,
"is_extractable": true,
"skill_nature": "LANGUAGE",
"slug": "html",
"sub_category_id": 1467,
"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": 1107,
"existing_alias_text": "CSS",
"input_term": "CSS",
"matched_canonical": {
"category_id": 6,
"display_name": "CSS",
"id": 623,
"is_also_category": false,
"is_extractable": true,
"skill_nature": "LANGUAGE",
"slug": "css",
"sub_category_id": 486,
"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": 2015,
"existing_alias_text": "Machine Learning",
"input_term": "Machine Learning",
"matched_canonical": {
"category_id": 2,
"display_name": "Machine Learning",
"id": 1356,
"is_also_category": false,
"is_extractable": true,
"skill_nature": "CONCEPT",
"slug": "machine-learning",
"sub_category_id": 1024,
"typical_lifespan": "EVERGREEN",
"volatility": "STABLE"
},
"matched_via": "alias"
}
],
"candidate_roles": [
{
"display_name": "Cloud Security Engineer",
"id": 23,
"rationale": null,
"role_archetype": null,
"slug": "cloud-security-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": "Fullstack Developer",
"id": 435,
"rationale": null,
"role_archetype": "Engineering",
"slug": "fullstack-developer",
"source": "db"
},
{
"display_name": "Engineering Manager",
"id": 121,
"rationale": null,
"role_archetype": null,
"slug": "engineering-manager",
"source": "db"
},
{
"display_name": "Cyber Security Engineer",
"id": 5,
"rationale": null,
"role_archetype": null,
"slug": "cybersecurity-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": "Hybrid Mobile Developer",
"id": 11,
"rationale": null,
"role_archetype": null,
"slug": "hybrid-mobile-developer",
"source": "db"
},
{
"display_name": "Angular Frontend Developer",
"id": 90,
"rationale": null,
"role_archetype": "Engineering",
"slug": "angular-frontend-developer",
"source": "db"
},
{
"display_name": "Frontend Developer",
"id": 7,
"rationale": null,
"role_archetype": null,
"slug": "frontend-engineer",
"source": "db"
},
{
"display_name": "Ionic Developer",
"id": 434,
"rationale": null,
"role_archetype": null,
"slug": "ionic-developer",
"source": "db"
},
{
"display_name": "Node.js Backend Developer",
"id": 82,
"rationale": null,
"role_archetype": "Engineering",
"slug": "node-backend-developer",
"source": "db"
},
{
"display_name": "React Frontend Developer",
"id": 89,
"rationale": null,
"role_archetype": "Engineering",
"slug": "react-frontend-developer",
"source": "db"
},
{
"display_name": "React Native Developer",
"id": 73,
"rationale": null,
"role_archetype": "Engineering",
"slug": "react-native-developer",
"source": "db"
},
{
"display_name": "Svelte Frontend Developer",
"id": 92,
"rationale": null,
"role_archetype": "Engineering",
"slug": "svelte-frontend-developer",
"source": "db"
},
{
"display_name": "Vue Frontend Developer",
"id": 91,
"rationale": null,
"role_archetype": "Engineering",
"slug": "vue-frontend-developer",
"source": "db"
},
{
"display_name": "Web Developer",
"id": 25,
"rationale": null,
"role_archetype": null,
"slug": "web-developer",
"source": "db"
},
{
"display_name": "WordPress Dev",
"id": 227,
"rationale": null,
"role_archetype": "Engineering",
"slug": "wordpress-dev",
"source": "db"
},
{
"display_name": "Drupal Dev",
"id": 228,
"rationale": null,
"role_archetype": "Engineering",
"slug": "drupal-dev",
"source": "db"
},
{
"display_name": "Sitecore Dev",
"id": 233,
"rationale": null,
"role_archetype": "Engineering",
"slug": "sitecore-dev",
"source": "db"
},
{
"display_name": "Shopify Dev",
"id": 230,
"rationale": null,
"role_archetype": "Engineering",
"slug": "shopify-dev",
"source": "db"
},
{
"display_name": "AI Engineer",
"id": 13,
"rationale": null,
"role_archetype": null,
"slug": "ai-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 0.22 does not contradict",
"role_archetype": null,
"slug": "data-engineer",
"source": "db"
},
"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"
},
{
"display_name": "Fullstack Developer",
"id": 435,
"rationale": null,
"role_archetype": "Engineering",
"slug": "fullstack-developer",
"source": "db"
}
]
},
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Programming Languages \u0026 DSLs",
"id": 475,
"rationale": "Oversee and guide the selection and effective use of programming and domain\u2010specific languages in software projects.",
"slug": "programming-languages-dsls",
"source": "db"
},
"input_skill": "Python",
"llm_role": null,
"roles_from_db": [
{
"display_name": "Engineering Manager",
"id": 121,
"rationale": null,
"role_archetype": null,
"slug": "engineering-manager",
"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",
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"rationale": null,
"role_archetype": null,
"slug": "ml-engineer",
"source": "db"
},
{
"display_name": "MLOps Engineer",
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"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",
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"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": "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",
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"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": "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",
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"role_archetype": "Engineering",
"slug": "angular-frontend-developer",
"source": "db"
},
{
"display_name": "Frontend Developer",
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"rationale": null,
"role_archetype": null,
"slug": "frontend-engineer",
"source": "db"
},
{
"display_name": "Ionic Developer",
"id": 434,
"rationale": null,
"role_archetype": null,
"slug": "ionic-developer",
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},
{
"display_name": "Node.js Backend Developer",
"id": 82,
"rationale": null,
"role_archetype": "Engineering",
"slug": "node-backend-developer",
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},
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"rationale": null,
"role_archetype": "Engineering",
"slug": "react-frontend-developer",
"source": "db"
},
{
"display_name": "React Native Developer",
"id": 73,
"rationale": null,
"role_archetype": "Engineering",
"slug": "react-native-developer",
"source": "db"
},
{
"display_name": "Svelte Frontend Developer",
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"rationale": null,
"role_archetype": "Engineering",
"slug": "svelte-frontend-developer",
"source": "db"
},
{
"display_name": "Vue Frontend Developer",
"id": 91,
"rationale": null,
"role_archetype": "Engineering",
"slug": "vue-frontend-developer",
"source": "db"
},
{
"display_name": "Web Developer",
"id": 25,
"rationale": null,
"role_archetype": null,
"slug": "web-developer",
"source": "db"
}
]
},
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "JavaScript for WordPress",
"id": 329,
"rationale": "Client-side scripting used to enhance WordPress themes, blocks, and admin/editor interactions. This includes modern JavaScript patterns as they apply to WordPress-specific behavior rather than standalone frontend applications.",
"slug": "javascript-for-wordpress",
"source": "db"
},
"input_skill": "JavaScript",
"llm_role": null,
"roles_from_db": [
{
"display_name": "WordPress Dev",
"id": 227,
"rationale": null,
"role_archetype": "Engineering",
"slug": "wordpress-dev",
"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": "JavaScript",
"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": "JavaScript",
"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",
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"role_archetype": null,
"slug": "full-stack-engineer",
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},
{
"display_name": "Fullstack Developer",
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}
]
},
{
"dimension": {
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"display_name": "Programming Languages \u0026 DSLs",
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"rationale": "Oversee and guide the selection and effective use of programming and domain\u2010specific languages in software projects.",
"slug": "programming-languages-dsls",
"source": "db"
},
"input_skill": "JavaScript",
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"roles_from_db": [
{
"display_name": "Engineering Manager",
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"role_archetype": null,
"slug": "engineering-manager",
"source": "db"
}
]
},
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Programming Languages \u0026 Template Languages",
"id": 359,
"rationale": "The languages and domain-specific templating languages used for Drupal development and theming.",
"slug": "programming-languages-template-languages",
"source": "db"
},
"input_skill": "JavaScript",
"llm_role": null,
"roles_from_db": [
{
"display_name": "Drupal Dev",
"id": 228,
"rationale": null,
"role_archetype": "Engineering",
"slug": "drupal-dev",
"source": "db"
}
]
},
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Sitecore Development Languages",
"id": 438,
"rationale": "Core implementation languages and markup used to build Sitecore customizations, rendering logic, and site behavior. This is the primary authoring surface for Sitecore-specific code and templates.",
"slug": "sitecore-development-languages",
"source": "db"
},
"input_skill": "JavaScript",
"llm_role": null,
"roles_from_db": [
{
"display_name": "Sitecore Dev",
"id": 233,
"rationale": null,
"role_archetype": "Engineering",
"slug": "sitecore-dev",
"source": "db"
}
]
},
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Storefront JavaScript and DOM Behavior",
"id": 422,
"rationale": "Client-side behavior used to enhance Shopify storefront interactions beyond static theme rendering. This includes interactive UI logic, event handling, and progressive enhancement within theme constraints.",
"slug": "storefront-javascript-and-dom-behavior",
"source": "db"
},
"input_skill": "JavaScript",
"llm_role": null,
"roles_from_db": [
{
"display_name": "Shopify Dev",
"id": 230,
"rationale": null,
"role_archetype": "Engineering",
"slug": "shopify-dev",
"source": "db"
}
]
}
],
"input_skill": "JavaScript",
"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": "HTML",
"alias_type": "CANONICAL",
"id": 2627,
"is_primary": true,
"match_strategy": "CASE_INSENSITIVE"
}
],
"canonical": {
"category_id": 6,
"display_name": "HTML",
"id": 1657,
"is_also_category": false,
"is_extractable": true,
"skill_nature": "LANGUAGE",
"slug": "html",
"sub_category_id": 1467,
"typical_lifespan": "EVERGREEN",
"volatility": "STABLE"
},
"dimensions": [
{
"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": "HTML",
"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 \u0026 Template Languages",
"id": 359,
"rationale": "The languages and domain-specific templating languages used for Drupal development and theming.",
"slug": "programming-languages-template-languages",
"source": "db"
},
"input_skill": "HTML",
"llm_role": null,
"roles_from_db": [
{
"display_name": "Drupal Dev",
"id": 228,
"rationale": null,
"role_archetype": "Engineering",
"slug": "drupal-dev",
"source": "db"
}
]
},
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "React Frontend Development",
"id": 96,
"rationale": "Building interactive web user interfaces with React.js, including component composition, state management, hooks, and rendering patterns. React.js belongs here because it is a core library for client-side UI development in modern web applications.",
"slug": "d_init_01",
"source": "db"
},
"input_skill": "HTML",
"llm_role": null,
"roles_from_db": []
},
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Sitecore Development Languages",
"id": 438,
"rationale": "Core implementation languages and markup used to build Sitecore customizations, rendering logic, and site behavior. This is the primary authoring surface for Sitecore-specific code and templates.",
"slug": "sitecore-development-languages",
"source": "db"
},
"input_skill": "HTML",
"llm_role": null,
"roles_from_db": [
{
"display_name": "Sitecore Dev",
"id": 233,
"rationale": null,
"role_archetype": "Engineering",
"slug": "sitecore-dev",
"source": "db"
}
]
}
],
"input_skill": "HTML",
"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": "CSS",
"alias_type": "CANONICAL",
"id": 1107,
"is_primary": true,
"match_strategy": "CASE_INSENSITIVE"
}
],
"canonical": {
"category_id": 6,
"display_name": "CSS",
"id": 623,
"is_also_category": false,
"is_extractable": true,
"skill_nature": "LANGUAGE",
"slug": "css",
"sub_category_id": 486,
"typical_lifespan": "EVERGREEN",
"volatility": "STABLE"
},
"dimensions": [
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "CSS Architecture and Styling",
"id": 117,
"rationale": "Styling systems and layout techniques used to create responsive, maintainable visual presentation in the browser. Frontend engineers need this to translate design intent into consistent interfaces.",
"slug": "css-architecture-and-styling",
"source": "db"
},
"input_skill": "CSS",
"llm_role": null,
"roles_from_db": [
{
"display_name": "Frontend Developer",
"id": 7,
"rationale": null,
"role_archetype": null,
"slug": "frontend-engineer",
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},
{
"display_name": "Fullstack Developer",
"id": 15,
"rationale": null,
"role_archetype": null,
"slug": "full-stack-engineer",
"source": "db"
},
{
"display_name": "Fullstack Developer",
"id": 435,
"rationale": null,
"role_archetype": "Engineering",
"slug": "fullstack-developer",
"source": "db"
},
{
"display_name": "React Frontend Developer",
"id": 89,
"rationale": null,
"role_archetype": "Engineering",
"slug": "react-frontend-developer",
"source": "db"
},
{
"display_name": "Svelte Frontend Developer",
"id": 92,
"rationale": null,
"role_archetype": "Engineering",
"slug": "svelte-frontend-developer",
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},
{
"display_name": "Vue Frontend Developer",
"id": 91,
"rationale": null,
"role_archetype": "Engineering",
"slug": "vue-frontend-developer",
"source": "db"
},
{
"display_name": "Web Developer",
"id": 25,
"rationale": null,
"role_archetype": null,
"slug": "web-developer",
"source": "db"
}
]
},
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Programming Languages \u0026 Template Languages",
"id": 359,
"rationale": "The languages and domain-specific templating languages used for Drupal development and theming.",
"slug": "programming-languages-template-languages",
"source": "db"
},
"input_skill": "CSS",
"llm_role": null,
"roles_from_db": [
{
"display_name": "Drupal Dev",
"id": 228,
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"role_archetype": "Engineering",
"slug": "drupal-dev",
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}
]
},
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Sitecore Development Languages",
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"rationale": "Core implementation languages and markup used to build Sitecore customizations, rendering logic, and site behavior. This is the primary authoring surface for Sitecore-specific code and templates.",
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},
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{
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}
]
},
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Storefront Styling and Responsive Layout",
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"rationale": "Visual presentation work for Shopify storefronts, including layout, spacing, typography, and responsive behavior. This is a coherent cluster because theme developers must translate commerce designs into usable storefront pages.",
"slug": "storefront-styling-and-responsive-layout",
"source": "db"
},
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{
"display_name": "Shopify Dev",
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}
]
},
{
"dimension": {
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"rationale": "Visual presentation techniques used to translate design requirements into usable Angular interfaces. This includes layout, theming, spacing, and responsive behavior across screen sizes.",
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},
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"roles_from_db": [
{
"display_name": "Angular Frontend Developer",
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"role_archetype": "Engineering",
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}
]
}
],
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"was_in_llm_skills": true
},
{
"aliases_in_db": [],
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"dimensions": [],
"input_skill": "Handlebars.js",
"matched_via": null,
"new_alias_persisted": false,
"new_alias_text": null,
"new_skill_meta": {
"derived": {
"category": "Web Frameworks",
"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": "handlebars-js",
"split_log": [],
"typed": null,
"warnings": []
},
"source_tag": "llm",
"was_in_llm_skills": true
},
{
"aliases_in_db": [
{
"alias_text": "Machine Learning",
"alias_type": "CANONICAL",
"id": 2015,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
}
],
"canonical": {
"category_id": 2,
"display_name": "Machine Learning",
"id": 1356,
"is_also_category": false,
"is_extractable": true,
"skill_nature": "CONCEPT",
"slug": "machine-learning",
"sub_category_id": 1024,
"typical_lifespan": "EVERGREEN",
"volatility": "STABLE"
},
"dimensions": [
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "AI Governance and Model Security",
"id": 50,
"rationale": "Controls and documentation used to make models safer, auditable, and compliant. ML engineers use this to manage model risk, supply chain integrity, and governance requirements.",
"slug": "ai-governance-and-model-security",
"source": "db"
},
"input_skill": "Machine Learning",
"llm_role": null,
"roles_from_db": [
{
"display_name": "AI Engineer",
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"role_archetype": null,
"slug": "ai-engineer",
"source": "db"
},
{
"display_name": "ML Engineer",
"id": 3,
"rationale": null,
"role_archetype": null,
"slug": "ml-engineer",
"source": "db"
},
{
"display_name": "MLOps Engineer",
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"rationale": null,
"role_archetype": null,
"slug": "ml-ops-engineer",
"source": "db"
}
]
},
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "React Frontend Development",
"id": 96,
"rationale": "Building interactive web user interfaces with React.js, including component composition, state management, hooks, and rendering patterns. React.js belongs here because it is a core library for client-side UI development in modern web applications.",
"slug": "d_init_01",
"source": "db"
},
"input_skill": "Machine Learning",
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"roles_from_db": []
}
],
"input_skill": "Machine Learning",
"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": [
"ETL",
"Palantir Foundry",
"Data Ingestion",
"Data Pipelines",
"Data Quality",
"Data Lineage",
"Spark SQL",
"Statistical Models",
"Data Health Checks",
"Handlebars.js"
]
}
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 0.22 does not contradict",
"role_archetype": null,
"slug": "data-engineer",
"source": "db"
},
"chosen_role_resolution": "in_db",
"final_input_skills": [
{
"skill": "ETL",
"tag": "new"
},
{
"skill": "Python",
"tag": "in_db"
},
{
"skill": "PySpark",
"tag": "in_db"
},
{
"skill": "Palantir Foundry",
"tag": "new"
},
{
"skill": "Data Ingestion",
"tag": "new"
},
{
"skill": "Data Pipelines",
"tag": "new"
},
{
"skill": "Data Quality",
"tag": "new"
},
{
"skill": "Data Lineage",
"tag": "new"
},
{
"skill": "Spark",
"tag": "in_db"
},
{
"skill": "Scala",
"tag": "in_db"
},
{
"skill": "Spark SQL",
"tag": "new"
},
{
"skill": "Statistical Models",
"tag": "new"
},
{
"skill": "Data Health Checks",
"tag": "new"
},
{
"skill": "Java",
"tag": "in_db"
},
{
"skill": "JavaScript",
"tag": "in_db"
},
{
"skill": "HTML",
"tag": "in_db"
},
{
"skill": "CSS",
"tag": "in_db"
},
{
"skill": "Handlebars.js",
"tag": "new"
},
{
"skill": "Machine Learning",
"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 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"
},
{
"display_name": "Fullstack Developer",
"id": 435,
"rationale": null,
"role_archetype": "Engineering",
"slug": "fullstack-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": "Programming Languages \u0026 DSLs",
"id": 475,
"rationale": "Oversee and guide the selection and effective use of programming and domain\u2010specific languages in software projects.",
"slug": "programming-languages-dsls",
"source": "db"
},
"dimension_id": 475,
"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": "Engineering Manager",
"id": 121,
"rationale": null,
"role_archetype": null,
"slug": "engineering-manager",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 5,
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},
{
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},
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{
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],
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{
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{
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},
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{
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{
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],
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},
{
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"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.",
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},
"dimension_id": 97,
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"roles_from_db": [
{
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],
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},
{
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"slug": "python-programming",
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},
"dimension_id": 290,
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"roles_from_db": [
{
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],
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{
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},
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"outcome_line": "Skipped \u2014 no persistable v3 meta for new skill",
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"roles_from_db": [
{
"display_name": "Data Engineer",
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}
],
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{
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"roles_from_db": [
{
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}
],
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},
{
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"roles_from_db": [
{
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}
],
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},
{
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},
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"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
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"roles_from_db": [
{
"display_name": "ML Engineer",
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},
{
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}
],
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},
{
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},
"dimension_id": 279,
"input_skill": "Java",
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"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
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"roles_from_db": [
{
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},
{
"display_name": "Kotlin Backend Developer",
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},
{
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],
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},
{
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},
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"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
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"roles_from_db": [
{
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}
],
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},
{
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"slug": "native-mobile-languages",
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},
"dimension_id": 274,
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"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
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"roles_from_db": [
{
"display_name": "Native Mobile Developer",
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],
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},
{
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},
"dimension_id": 267,
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"matched_chosen_role": false,
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"roles_from_db": [
{
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],
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},
{
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},
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{
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{
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{
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],
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},
{
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},
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"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
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"roles_from_db": [
{
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],
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},
{
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{
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},
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{
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],
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},
{
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},
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"roles_from_db": [
{
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{
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{
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{
"display_name": "Node.js Backend Developer",
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{
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{
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{
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{
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],
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},
{
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},
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"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
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{
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],
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],
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},
{
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{
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{
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{
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LLM Calls
Every model call made for this run, in pipeline order. Click a card to see the model's response.