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Pipeline run

13c0eb73-def6-461d-9429-7e9a6d29af3d

Pipeline LLM cost (USD)
API 1: $0.0076 API 2: $0.0002 API 3: $0.0000 Total: $0.0078

Client output enrichment

v2 Skill cluster · Nature of work · AI index · Tech stack maturity · Evidence · KRA description
role baseline loaded sources · ai_index: jd · nature_of_work: jd · tech_stack_maturity: jd
Nature of work · Data pipeline development
Build REST-based Scala microservices and related tools, using functional programming plus SQL/NoSQL, while applying ML/information-retrieval and big-data tech like Spark/Kafka/Elasticsearch when needed.
"Experience in building modern and scalable REST – based microservices using Scala"
Tech stack maturity
Mainstream Modern
The mix of Scala, microservices, REST, NoSQL, SQL, and machine learning indicates a contemporary, production-oriented stack that is widely adopted but not bleeding-edge or legacy.
AI index (0 = no AI use, 5 = totally AI-dependent · v2.1)
1.70 / 5
· Title match
Has AI skill
AI skill (primary)
· AI skill (secondary)
· On AI team
· Builds AI products
vocab breakdown (legacy)
Assistants (×1):
Frameworks (×2):
Models / concepts (×3): ML, Machine Learning
Evidence — skills matched in JD (17)
REST Microservices Scala Functional Programming NoSQL SQL Machine Learning Big Data Data Structures and Algorithms Play MVC Java Apache Spark ML Kafka Elasticsearch Python
Skill cluster (8 dimension groups, role-scoped)
Programming Languages for Data Work
Scala SQL Java Python
AI Governance and Model Security
Machine Learning
Application Architecture and Code Organization
MVC
ETL and ELT Tooling
Apache Spark
Integration Protocols & Standards
REST
Messaging and Event Streaming
Kafka
Search and Content Discovery
Elasticsearch
Cross-cutting / unaligned
Microservices Functional Programming NoSQL Big Data Data Structures and Algorithms Play ML
Show KRA description ↓
• Experience in building modern and scalable REST – based microservices using Scala, preferably with Play as MVC framework. • Expertise with functional programming using Scala • Experience in implementing RESTful web services in Scala, Java or similar languages • Experience with No SQL and SQL databases • Experience in information retrieval and machine learning • Experience/ knowledge in big data using Scala spark, ML, Kafka, Elastic search will be plus. • 5/6 to 8/9 years with 2+ Years of relevant Experience in Big data • Technology graduate from reputed institute • Should have tool development using Python or Scala. • Most importantly should be strong in Data Structures and Algorithms. • Should have worked in product companies only.

Signals

Skill backend-engineer
0.33
Alias
KRA data-engineer
0.48

Post-classification

Centroidupdated · n=58
Alias collision log
New-role queue
New skills captured5
New KRA captured

Captured for admin review

Play Data Engineer pending
Functional Programming primary Data Engineer pending
ML Data Engineer pending
Big Data primary Data Engineer pending
Data Structures and Algorithms primary Data Engineer pending
Status: completed Created: 2026-05-27T13:40:08.908002Z Updated: 2026-05-27T13:42:33.469113Z API 3 duration: 70108 ms
Flow Current 3-step pipeline

1 POST /skills/extract-from-jd

2 POST /skills/extract-details

3 POST /skills/final-role-output

Role Chosen role & resolution

Data Engineer

domain · Data Engineering & Analytics CASE DOMAIN

slug: data-engineer · id: 2 · source: db

Domain=Data Engineering & Analytics; The JD is centered on Scala-based microservices, big data tooling, Kafka/Spark/ElasticSearch, and tool development, which best matches a Data Engineer profile rather than analytics or warehouse-specific roles.

Matched skills

ScalaPlayRESTfunctional programmingSQLNo SQLmachine learningScala sparkKafkaElastic searchPythonData Structures and Algorithms

Matched dimensions

Microservices DevelopmentBig Data EngineeringRESTful API DevelopmentProgramming Language ProficiencySearch and Machine Learning IntegrationAlgorithmic Problem Solving

Matched KRAs

building modern and scalable REST-based microservicesimplementing RESTful web services in Scala, Java or similar languagesexperience with No SQL and SQL databasesexperience in information retrieval and machine learningtool development using Python or Scala

Resolution: in_db — role exists in library; skill↔dim and role↔dim links saved when applicable.

0
New skills
0
Skill↔dim saved
0
Role↔dim saved
1
Skipped

Job description

Company Description
Cogent Integrated Business Solutions Inc. is a global technology company with offices in the USA, Spain, and India. As an SAP partner, we specialize in providing niche SAP project/consulting services and Enterprise Mobility services. Cogent Integrated Business Solutions takes pride in the quality of work done and prioritizes customers above everything else.


Requirement
• Experience in building modern and scalable REST – based microservices using Scala, preferably with Play as MVC framework.
• Expertise with functional programming using Scala
• Experience in implementing RESTful web services in Scala, Java or similar languages 
•  Experience with No SQL and SQL databases
• Experience in information retrieval and machine learning
• Experience/ knowledge in big data using Scala spark, ML, Kafka, Elastic search will be plus. 


Experience:  
• 5/6 to 8/9 years with 2+ Years of relevant Experience in Big data
• Technology graduate from reputed institute
• Should have tool development using Python or Scala.
• Most importantly should be strong in Data Structures and Algorithms.
• Should have worked in product companies only.
• 

In case you are interested, kindly share your resume at shreya.g@cogentibs.in (What's app no. (+91 9911699381)

Skills from this JD

Each row merges API 1 extraction, API 2 library match / v3 orchestration (dimensions + locked dims), and API 3 persistence tags.

REST Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: REST id=11 · rest

Aliases — catalog

  • REST (CANONICAL) primary

Context tags (catalog)

API API design API versioning CRUD DELETE GET HATEOAS HTTP JSON OAuth OAuth2 OpenAPI POST PUT Postman RESTful Swagger URI Webhooks XML authentication client-server content negotiation endpoint endpoints middleware resource resource-oriented serialization stateless status codes versioning web services

Stored enrichment (catalog DB)

Category
Concept
Sub-category
Api Architecture Style
Year introduced
2000
Confidence
0.88
Version strategy
NOT_APPLICABLE

Maturity reasoning: REST is a default API architecture in many job descriptions and is widely supported by major vendors/frameworks; OpenAPI and RESTful endpoints remain standard in hiring pipelines.

Skill profile (library / DB)

Skill nature
CONCEPT
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
2
Sub-category id
2122
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • API Design and Contracts Catalog dimension db id 3

    Library dimension (catalog)

    Roles linked in library: Backend Developer, Fullstack Developer

  • API Interface and Contract Design Catalog dimension db id 289

    Library dimension (catalog)

    Roles linked in library: .NET Backend Developer, Go Backend Developer, Kotlin Backend Developer, Node.js Backend Developer, PHP Backend Developer, Python Backend Developer, Ruby Backend Developer, Scala Backend Developer

  • Integration Protocols & Standards Catalog dimension db id 271

    Library dimension (catalog)

    Roles linked in library: Pega Developer

  • Standards & Protocols Compliance Catalog dimension db id 452

    Library dimension (catalog)

    Roles linked in library: Sitecore Dev

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
API Design and Contracts
api-design-and-contracts
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
API Interface and Contract Design
api-interface-and-contract-design
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Integration Protocols & Standards
integration-protocols-standards
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Standards & Protocols Compliance
standards-protocols-compliance
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Microservices Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: microservices id=41 · microservices

Aliases — catalog

  • microservices (CANONICAL) primary

Context tags (catalog)

API Gateway API gateway CQRS DevOps Docker Kubernetes REST API RESTful services Saga pattern Spring Boot circuit breaker containerization decentralized distributed tracing domain-driven design event sourcing event-driven event-driven architecture gRPC load balancing message broker microservices patterns monitoring scalability service discovery service mesh

Stored enrichment (catalog DB)

Category
Architecture
Sub-category
Distributed System Architecture
Confidence
0.99
Version strategy
NOT_APPLICABLE

Maturity reasoning: Microservices is a common architecture in job descriptions across backend/cloud roles, and major vendors like AWS, Google Cloud, and Kubernetes ecosystems provide first-class support and reference patterns.

Skill profile (library / DB)

Skill nature
PATTERN
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
1
Sub-category id
1
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • Microservices and Distributed Systems Catalog dimension db id 9

    Library dimension (catalog)

    Roles linked in library: Backend Developer, Node.js Backend Developer, Scala Backend Developer

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
Microservices and Distributed Systems
microservices-and-distributed-systems
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Scala Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: Scala id=102 · scala

Aliases — catalog

  • Scala (CANONICAL) primary

Context tags (catalog)

Akka Apache Kafka Cats Flink JVM Monads Play Framework SBT ScalaTest Shapeless Spark Spark SQL ZIO case class for-comprehension functional programming implicit pattern matching typeclass

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)
Play Secondary New / orchestrated API 3: new canonical path (new) New / unmatched skill (orchestrated in API 2)

Skill enrichment (orchestrator / LLM)

No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).

Derived legacy fields
Category
Programming Languages
Sub-category
general
Skill nature
LANGUAGE
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
MVC Secondary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: MVC id=505 · mvc

Aliases — catalog

  • MVC (CANONICAL) primary

Context tags (catalog)

ASP.NET ASP.NET MVC Angular Backend Controller Data binding Dependency injection Express.js Flask Frontend Laravel Model Model-View-Controller RESTful Rails React Routing Ruby on Rails Separation of concerns Spring MVC UI components View action methods controller data binding dependency injection event handling layout pages model partial views routing separation of concerns state management template engine templating view

Stored enrichment (catalog DB)

Category
Architecture
Sub-category
Model View Controller
Year introduced
1979
Confidence
0.93
Version strategy
NOT_APPLICABLE

Maturity reasoning: MVC remains a standard web/app architecture in many job descriptions and frameworks (e.g., ASP.NET MVC, Spring MVC, Rails), with no vendor sunset or replacement making it obsolete.

Skill profile (library / DB)

Skill nature
PATTERN
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
1
Sub-category id
2462
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • ASP.NET Core Web Frameworks Catalog dimension db id 363

    Library dimension (catalog)

    Roles linked in library: .NET Backend Developer

  • App Architecture and Dependency Injection Catalog dimension db id 94

    Library dimension (catalog)

    Roles linked in library: Android Developer, iOS Developer

  • Application Architecture and Code Organization Catalog dimension db id 220

    Library dimension (catalog)

    Roles linked in library: Fullstack Developer

  • Native Mobile App Architecture and Dependency Injection Catalog dimension db id 273

    Library dimension (catalog)

    Roles linked in library: Native Mobile Developer

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
ASP.NET Core Web Frameworks
asp-net-core-web-frameworks
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
App Architecture and Dependency Injection
app-architecture-and-dependency-injection
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Application Architecture and Code Organization
application-architecture-and-code-organization
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Native Mobile App Architecture and Dependency Injection
native-mobile-app-architecture-and-dependency-injection
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Functional Programming Primary New / orchestrated API 3: new canonical path (new) New / unmatched skill (orchestrated in API 2)

Skill enrichment (orchestrator / LLM)

No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).

Derived legacy fields
Category
Concepts
Sub-category
general
Skill nature
CONCEPT
Volatility
STABLE
Typical lifespan
EVERGREEN
Version strategy
UNVERSIONED
Java Secondary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: Java id=1 · java

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)

APIs Apache Tomcat Concurrency Design patterns Garbage collection GraalVM Gradle Hibernate JDBC JDK JPA JUnit JVM Java 8 Java EE JavaFX Kafka Lambda expressions Maven Microservices Mockito Object-oriented REST RESTful SOAP Servlets Spring Spring Boot Tomcat microservices

Stored enrichment (catalog DB)

Category
Language
Sub-category
Programming Language
Vendor
Oracle
License
other_open
Year introduced
1995
Confidence
0.99
Version strategy
SEPARATE_ENTITY
Version tag
21

Maturity reasoning: Java is a hiring-pipeline staple with very high JD volume across enterprise backend, Android, and cloud roles; it remains widely supported by major vendors and frameworks like Spring.

Skill profile (library / DB)

Skill nature
LANGUAGE
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
6
Sub-category id
96
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • Java Language and JVM Catalog dimension db id 279

    Library dimension (catalog)

    Roles linked in library: Java Backend Developer, Kotlin Backend Developer, Scala Backend Developer

  • Kotlin and Java Catalog dimension db id 161

    Library dimension (catalog)

    Roles linked in library: Android Developer

  • Native Mobile Languages Catalog dimension db id 274

    Library dimension (catalog)

    Roles linked in library: Native Mobile Developer

  • Pega Programming Languages & DSLs Catalog dimension db id 267

    Library dimension (catalog)

    Roles linked in library: Pega Developer

  • Programming Languages Catalog dimension db id 1

    Library dimension (catalog)

    Roles linked in library: Backend Developer, Fullstack Developer

  • Programming Languages for Data Work Catalog dimension db id 21

    Library dimension (catalog)

    Roles linked in library: Data Engineer

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
Java Language and JVM
java-language-and-jvm
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Kotlin and Java
kotlin-and-java
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Native Mobile Languages
native-mobile-languages
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Pega Programming Languages & DSLs
pega-programming-languages-dsls
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Programming Languages
programming-languages
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Programming Languages for Data Work
programming-languages-for-data-work
Existing dimension (library) · Role↔dimension saved
NoSQL Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: NoSQL id=1346 · nosql

Aliases — catalog

  • NoSQL (CANONICAL)

Context tags (catalog)

CAP theorem Cassandra DynamoDB MongoDB Redis column-family data modeling document store eventual consistency graph database horizontal scaling key-value store query language schema-less sharding

Stored enrichment (catalog DB)

Category
Concept
Sub-category
Database Paradigm
Confidence
0.93
Version strategy
NOT_APPLICABLE

Maturity reasoning: NoSQL is broadly listed in job descriptions across backend/data roles, with MongoDB, DynamoDB, and Cassandra appearing as common market signals; it remains a hiring-pipeline staple rather than a niche or sunset tech.

Skill profile (library / DB)

Skill nature
CONCEPT
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
2
Sub-category id
1019
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • NoSQL Databases Catalog dimension db id 19

    Library dimension (catalog)

    Roles linked in library: Backend Developer

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
NoSQL Databases
nosql-databases
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
SQL Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: SQL id=101 · sql

Aliases — catalog

  • SQL (CANONICAL) primary

Context tags (catalog)

ACID CTE DDL DML ETL JOIN MySQL NoSQL OLAP ORM PostgreSQL SQL injection SQLite T-SQL data modeling data warehousing database normalization execution plan indexing joins normalization query optimization stored procedures subquery transaction isolation transaction management window functions

Stored enrichment (catalog DB)

Category
Language
Sub-category
Query Language
Vendor
ANSI
License
unknown
Year introduced
1974
Confidence
0.99
Version strategy
NOT_APPLICABLE

Maturity reasoning: SQL appears in a large share of data, backend, and analytics job descriptions and remains the default query language for PostgreSQL, MySQL, and cloud warehouses like Snowflake/BigQuery.

Skill profile (library / DB)

Skill nature
LANGUAGE
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
6
Sub-category id
97
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 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
Pega Programming Languages & DSLs
pega-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
Machine Learning Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: Machine Learning id=1356 · machine-learning

Aliases — catalog

  • Machine Learning (CANONICAL)

Context tags (catalog)

Keras PyTorch TensorFlow cross-validation data preprocessing ensemble methods feature engineering hyperparameter tuning model evaluation natural language processing neural networks reinforcement learning scikit-learn supervised learning unsupervised learning

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)
Apache Spark Secondary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: Apache Spark id=1350 · apache-spark

Aliases — catalog

  • Apache Spark (CANONICAL)
  • apache spark 3 (VERSION)
  • spark (VERSION)
  • spark 3 (VERSION)
  • spark 3.x (VERSION)
  • spark3 (VERSION)

Context tags (catalog)

Apache Kafka Cluster Manager DAGScheduler Data Lake DataFrame ETL Hadoop MLlib Machine Learning PySpark RDD Scala Spark SQL Spark Streaming SparkSession

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
ML Secondary New / orchestrated API 3: new canonical path (new) New / unmatched skill (orchestrated in API 2)

Skill enrichment (orchestrator / LLM)

No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).

Derived legacy fields
Category
Machine Learning Frameworks
Sub-category
general
Skill nature
CONCEPT
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
Kafka Secondary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: Kafka id=36 · kafka

Aliases — catalog

  • Kafka (CANONICAL) primary

Context tags (catalog)

Apache Flink Apache Kafka Apache Pulsar Apache Spark Avro KSQL Kafka API Kafka Connect Kafka Streams ZooKeeper Zookeeper backpressure brokers consumer consumer group consumer groups event sourcing event-driven architecture exactly-once semantics fault tolerance high throughput log compaction message broker message queue microservices offsets partition partitioning partitions producer producer API real-time analytics real-time data replication schema registry stream processing topic topic partitioning topics

Stored enrichment (catalog DB)

Category
Datastore
Sub-category
Event Stream Store
Vendor
Confluent
License
apache_2
Year introduced
2011
Confidence
0.90
Version strategy
NOT_APPLICABLE

Maturity reasoning: Kafka appears in many production JDs for event streaming and data pipelines, and remains a standard platform in cloud/vendor offerings (e.g., Confluent, AWS MSK), indicating broad hiring demand.

Skill profile (library / DB)

Skill nature
TOOL
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
3
Sub-category id
3533
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • Asynchronous Messaging and Event Streaming Catalog dimension db id 297

    Library dimension (catalog)

    Roles linked in library: .NET Backend Developer, Go Backend Developer, Kotlin Backend Developer, Node.js Backend Developer, Scala Backend Developer

  • Messaging and Background Jobs Catalog dimension db id 291

    Library dimension (catalog)

    Roles linked in library: PHP Backend Developer, Python Backend Developer, Ruby Backend Developer

  • Messaging and Event Streaming Catalog dimension db id 8

    Library dimension (catalog)

    Roles linked in library: Backend Developer, Data Engineer

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
Asynchronous Messaging and Event Streaming
asynchronous-messaging-and-event-streaming
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Messaging and Background Jobs
messaging-and-background-jobs
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Messaging and Event Streaming
messaging-and-event-streaming
Existing dimension (library) · Role↔dimension saved
Elasticsearch Secondary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: Elasticsearch id=3171 · elasticsearch

Aliases — catalog

  • Elasticsearch (CANONICAL) primary
  • ES (VERSION)
  • ElasticSearch (VERSION)
  • Elasticsearch 6 (VERSION)
  • Elasticsearch 6.x (VERSION)
  • Elasticsearch 7 (VERSION)
  • Elasticsearch 7.x (VERSION)
  • Elasticsearch 8 (VERSION)
  • Elasticsearch 8.x (VERSION)
  • Elasticsearch v6 (VERSION)
  • Elasticsearch v7 (VERSION)
  • Elasticsearch v8 (VERSION)

Context tags (catalog)

ELK stack JSON Kibana Logstash Lucene REST API RESTful API aggregation cluster management data visualization document store full-text search indexing performance tuning query DSL real-time search replication scalability search analytics search relevance sharding

Stored enrichment (catalog DB)

Category
Datastore
Sub-category
Search Datastore
Vendor
Elastic NV
License
apache_2
Year introduced
2010
Confidence
0.93
Version strategy
SEPARATE_ENTITY
Version tag
8.x

Maturity reasoning: Commonly listed in job descriptions for search/log analytics roles and widely deployed in production; Elastic’s docs and ecosystem show sustained adoption rather than sunset or replacement.

Skill profile (library / DB)

Skill nature
TOOL
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
3
Sub-category id
2925
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • Magento Search and Indexing Catalog dimension db id 403

    Library dimension (catalog)

    Roles linked in library: Magento Dev

  • Search and Content Discovery Catalog dimension db id 356

    Library dimension (catalog)

    Roles linked in library: Drupal Dev, Sitecore Dev

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
Magento Search and Indexing
magento-search-and-indexing
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Search and Content Discovery
search-and-content-discovery
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Big Data Primary New / orchestrated API 3: new canonical path (new) New / unmatched skill (orchestrated in API 2)

Skill enrichment (orchestrator / LLM)

No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).

Derived legacy fields
Category
Data Engineering Tools
Sub-category
general
Skill nature
CONCEPT
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
Python Secondary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: Python id=5 · python

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)

API Django FastAPI Flask Jupyter NumPy PEP 8 Pandas REST SQLAlchemy asyncio pandas pip pytest type hints venv virtualenv

Stored enrichment (catalog DB)

Category
Language
Sub-category
Programming Language
Vendor
PSF
License
mit
Year introduced
1991
Confidence
0.99
Version strategy
SEPARATE_ENTITY
Version tag
3

Maturity reasoning: Python appears in a very high volume of job descriptions across data, backend, automation, and ML roles, and remains a default hiring-pipeline language on major job boards and tech stacks.

Skill profile (library / DB)

Skill nature
LANGUAGE
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
6
Sub-category id
96
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • Cloud Security Scripting & DSL Languages Catalog dimension db id 248

    Library dimension (catalog)

    Roles linked in library: Cloud Security Engineer

  • Programming Languages Catalog dimension db id 1

    Library dimension (catalog)

    Roles linked in library: Backend Developer, Fullstack Developer

  • Programming Languages and Scripting Catalog dimension db id 59

    Library dimension (catalog)

    Roles linked in library: Cyber Security Engineer

  • Programming Languages for Data Work Catalog dimension db id 21

    Library dimension (catalog)

    Roles linked in library: Data Engineer

  • Programming Languages for ML Systems Catalog dimension db id 39

    Library dimension (catalog)

    Roles linked in library: ML Engineer, MLOps Engineer

  • Programming Languages for XR Catalog dimension db id 97

    Library dimension (catalog)

    Roles linked in library: AR/VR Engineer

  • Python Programming Catalog dimension db id 290

    Library dimension (catalog)

    Roles linked in library: Python Backend Developer

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
Cloud Security Scripting & DSL Languages
cloud-security-scripting-dsl-languages
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Programming Languages
programming-languages
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Programming Languages and Scripting
programming-languages-and-scripting
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Programming Languages for Data Work
programming-languages-for-data-work
Existing dimension (library) · Role↔dimension saved
Programming Languages for ML Systems
programming-languages-for-ml-systems
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Programming Languages for XR
programming-languages-for-xr
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Python Programming
python-programming
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Data Structures and Algorithms Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: Data Structures id=1003 · data-structures

Aliases — catalog

  • Data Structures (CANONICAL)

Context tags (catalog)

Big O notation arrays binary search complexity analysis dynamic programming graphs hash tables linked lists memory management queues recursion searching algorithms sorting algorithms stacks trees

Stored enrichment (catalog DB)

Category
Concept
Sub-category
Data Structures
Confidence
0.98
Version strategy
NOT_APPLICABLE

Maturity reasoning: Core CS concept in nearly all software engineering JDs and interview loops; widely taught and expected across roles, with no sunset or replacement signal.

Skill profile (library / DB)

Skill nature
CONCEPT
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
2
Sub-category id
731
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • React Frontend Development Catalog dimension db id 96

    Library dimension (catalog)

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
React Frontend Development
d_init_01
Skipped — no persistable v3 meta for new skill
skill_not_in_db_v3_proposed

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
REST in_db
API Design and Contracts
api-design-and-contracts
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
REST in_db
API Interface and Contract Design
api-interface-and-contract-design
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
REST in_db
Integration Protocols & Standards
integration-protocols-standards
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
REST in_db
Standards & Protocols Compliance
standards-protocols-compliance
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Microservices in_db
Microservices and Distributed Systems
microservices-and-distributed-systems
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
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)
MVC in_db
ASP.NET Core Web Frameworks
asp-net-core-web-frameworks
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
MVC in_db
App Architecture and Dependency Injection
app-architecture-and-dependency-injection
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
MVC in_db
Application Architecture and Code Organization
application-architecture-and-code-organization
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
MVC in_db
Native Mobile App Architecture and Dependency Injection
native-mobile-app-architecture-and-dependency-injection
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Java in_db
Java Language and JVM
java-language-and-jvm
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Java in_db
Kotlin and Java
kotlin-and-java
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Java in_db
Native Mobile Languages
native-mobile-languages
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Java in_db
Pega Programming Languages & DSLs
pega-programming-languages-dsls
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Java in_db
Programming Languages
programming-languages
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Java in_db
Programming Languages for Data Work
programming-languages-for-data-work
Existing dimension (library) · Role↔dimension saved
NoSQL in_db
NoSQL Databases
nosql-databases
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
SQL in_db
Pega Programming Languages & DSLs
pega-programming-languages-dsls
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
SQL in_db
Programming Languages for Data Work
programming-languages-for-data-work
Existing dimension (library) · Role↔dimension saved
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)
Apache Spark in_db
ETL and ELT Tooling
etl-and-elt-tooling
Existing dimension (library) · Role↔dimension saved
Kafka in_db
Asynchronous Messaging and Event Streaming
asynchronous-messaging-and-event-streaming
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Kafka in_db
Messaging and Background Jobs
messaging-and-background-jobs
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Kafka in_db
Messaging and Event Streaming
messaging-and-event-streaming
Existing dimension (library) · Role↔dimension saved
Elasticsearch in_db
Magento Search and Indexing
magento-search-and-indexing
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Elasticsearch in_db
Search and Content Discovery
search-and-content-discovery
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Python in_db
Cloud Security Scripting & DSL Languages
cloud-security-scripting-dsl-languages
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Python in_db
Programming Languages
programming-languages
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Python in_db
Programming Languages and Scripting
programming-languages-and-scripting
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Python in_db
Programming Languages for Data Work
programming-languages-for-data-work
Existing dimension (library) · Role↔dimension saved
Python in_db
Programming Languages for ML Systems
programming-languages-for-ml-systems
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Python in_db
Programming Languages for XR
programming-languages-for-xr
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Python in_db
Python Programming
python-programming
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Data Structures and Algorithms new
React Frontend Development
d_init_01
Skipped — no persistable v3 meta for new skill skill_not_in_db_v3_proposed

Library artifacts (this run)

Kind Detail DB id
canonical_skill_proposed Play | type=Programming Languages subtype=general nature=LANGUAGE lifespan=MULTI_YEAR
canonical_skill_proposed Functional Programming | type=Concepts subtype=general nature=CONCEPT lifespan=EVERGREEN
canonical_skill_proposed ML | type=Machine Learning Frameworks subtype=general nature=CONCEPT lifespan=MULTI_YEAR
canonical_skill_proposed Big Data | type=Data Engineering Tools subtype=general nature=CONCEPT lifespan=MULTI_YEAR
dimension_skill_link_proposed Data Structures and Algorithms ↔ React Frontend Development
nano JD Parser — gpt-4.1-nano click to toggle
CompanyCogent Integrated Business Solutions Inc.
Experience5/6 to 8/9 years with 2+ Years of relevant Experience in Big data
DomainIT Services & Consulting
JD type pass
Show raw JSON
{
  "JD_type": "pass",
  "about_company": {
    "source_marker": {
      "first_5_words": "Cogent Integrated Business Solutions",
      "last_5_words": "customers above everything else."
    },
    "text": "Cogent Integrated Business Solutions Inc. is a global technology company with offices in the USA, Spain, and India. As an SAP partner, we specialize in providing niche SAP project/consulting services and Enterprise Mobility services. Cogent Integrated Business Solutions takes pride in the quality of work done and prioritizes customers above everything else.",
    "word_count": 54
  },
  "archetype_override_applied": true,
  "archetype_override_matched_skills": [
    "Python",
    "Scala",
    "Algorithms",
    "Data Structures",
    "Machine Learning",
    "Java",
    "MVC",
    "SQL",
    "REST",
    "microservices",
    "Kafka"
  ],
  "certifications": [],
  "company_name": "Cogent Integrated Business Solutions Inc.",
  "ctc": null,
  "domain": {
    "primary": {
      "aliases": [],
      "domain": "IT Services \u0026 Consulting"
    },
    "secondary": null
  },
  "education": [
    {
      "level": "Bachelor\u0027s",
      "qualification": "Bachelor\u0027s - Technology",
      "raw": "Technology graduate from reputed institute",
      "requirement": "required"
    }
  ],
  "experience": {
    "max": 9,
    "min": 5,
    "raw": "5/6 to 8/9 years with 2+ Years of relevant Experience in Big data"
  },
  "job_locations": [],
  "role": null,
  "role_aliases": [],
  "role_archetype": "Engineering",
  "roles_and_responsibilities": [
    {
      "bullet_count": 6,
      "heading": "Requirement",
      "heading_was_present": true,
      "source_marker": {
        "first_5_words": "\u2022 Experience in building modern",
        "last_5_words": "ML, Kafka, Elastic search will"
      },
      "text": "\u2022 Experience in building modern and scalable REST \u2013 based microservices using Scala, preferably with Play as MVC framework.\n\u2022 Expertise with functional programming using Scala\n\u2022 Experience in implementing RESTful web services in Scala, Java or similar languages \n\u2022 Experience with No SQL and SQL databases\n\u2022 Experience in information retrieval and machine learning\n\u2022 Experience/ knowledge in big data using Scala spark, ML, Kafka, Elastic search will be plus.",
      "word_count": 56
    },
    {
      "bullet_count": 5,
      "heading": "Experience",
      "heading_was_present": true,
      "source_marker": {
        "first_5_words": "\u2022 5/6 to 8/9 years with",
        "last_5_words": "have worked in product companies only."
      },
      "text": "\u2022 5/6 to 8/9 years with 2+ Years of relevant Experience in Big data\n\u2022 Technology graduate from reputed institute\n\u2022 Should have tool development using Python or Scala.\n\u2022 Most importantly should be strong in Data Structures and Algorithms.\n\u2022 Should have worked in product companies only.",
      "word_count": 49
    }
  ],
  "urls": []
}
API 1 — extract-from-jd click to toggle
{
  "final_skills": [
    {
      "is_primary": true,
      "skill_name": "REST"
    },
    {
      "is_primary": true,
      "skill_name": "Microservices"
    },
    {
      "is_primary": true,
      "skill_name": "Scala"
    },
    {
      "is_primary": false,
      "skill_name": "Play"
    },
    {
      "is_primary": false,
      "skill_name": "MVC"
    },
    {
      "is_primary": true,
      "skill_name": "Functional Programming"
    },
    {
      "is_primary": false,
      "skill_name": "Java"
    },
    {
      "is_primary": true,
      "skill_name": "NoSQL"
    },
    {
      "is_primary": true,
      "skill_name": "SQL"
    },
    {
      "is_primary": true,
      "skill_name": "Machine Learning"
    },
    {
      "is_primary": false,
      "skill_name": "Apache Spark"
    },
    {
      "is_primary": false,
      "skill_name": "ML"
    },
    {
      "is_primary": false,
      "skill_name": "Kafka"
    },
    {
      "is_primary": false,
      "skill_name": "Elasticsearch"
    },
    {
      "is_primary": true,
      "skill_name": "Big Data"
    },
    {
      "is_primary": false,
      "skill_name": "Python"
    },
    {
      "is_primary": true,
      "skill_name": "Data Structures and Algorithms"
    }
  ],
  "jd_role": null,
  "nano_parsed": {
    "JD_type": "pass",
    "about_company": {
      "source_marker": {
        "first_5_words": "Cogent Integrated Business Solutions",
        "last_5_words": "customers above everything else."
      },
      "text": "Cogent Integrated Business Solutions Inc. is a global technology company with offices in the USA, Spain, and India. As an SAP partner, we specialize in providing niche SAP project/consulting services and Enterprise Mobility services. Cogent Integrated Business Solutions takes pride in the quality of work done and prioritizes customers above everything else.",
      "word_count": 54
    },
    "archetype_override_applied": true,
    "archetype_override_matched_skills": [
      "Python",
      "Scala",
      "Algorithms",
      "Data Structures",
      "Machine Learning",
      "Java",
      "MVC",
      "SQL",
      "REST",
      "microservices",
      "Kafka"
    ],
    "certifications": [],
    "company_name": "Cogent Integrated Business Solutions Inc.",
    "ctc": null,
    "domain": {
      "primary": {
        "aliases": [],
        "domain": "IT Services \u0026 Consulting"
      },
      "secondary": null
    },
    "education": [
      {
        "level": "Bachelor\u0027s",
        "qualification": "Bachelor\u0027s - Technology",
        "raw": "Technology graduate from reputed institute",
        "requirement": "required"
      }
    ],
    "experience": {
      "max": 9,
      "min": 5,
      "raw": "5/6 to 8/9 years with 2+ Years of relevant Experience in Big data"
    },
    "job_locations": [],
    "role": null,
    "role_aliases": [],
    "role_archetype": "Engineering",
    "roles_and_responsibilities": [
      {
        "bullet_count": 6,
        "heading": "Requirement",
        "heading_was_present": true,
        "source_marker": {
          "first_5_words": "\u2022 Experience in building modern",
          "last_5_words": "ML, Kafka, Elastic search will"
        },
        "text": "\u2022 Experience in building modern and scalable REST \u2013 based microservices using Scala, preferably with Play as MVC framework.\n\u2022 Expertise with functional programming using Scala\n\u2022 Experience in implementing RESTful web services in Scala, Java or similar languages \n\u2022 Experience with No SQL and SQL databases\n\u2022 Experience in information retrieval and machine learning\n\u2022 Experience/ knowledge in big data using Scala spark, ML, Kafka, Elastic search will be plus.",
        "word_count": 56
      },
      {
        "bullet_count": 5,
        "heading": "Experience",
        "heading_was_present": true,
        "source_marker": {
          "first_5_words": "\u2022 5/6 to 8/9 years with",
          "last_5_words": "have worked in product companies only."
        },
        "text": "\u2022 5/6 to 8/9 years with 2+ Years of relevant Experience in Big data\n\u2022 Technology graduate from reputed institute\n\u2022 Should have tool development using Python or Scala.\n\u2022 Most importantly should be strong in Data Structures and Algorithms.\n\u2022 Should have worked in product companies only.",
        "word_count": 49
      }
    ],
    "urls": []
  },
  "rejected": false,
  "rejection_reason": null,
  "run_id": "13c0eb73-def6-461d-9429-7e9a6d29af3d",
  "stage3_signals": {
    "alias_found": false,
    "alias_match_roles": [],
    "kra_match_roles": [
      {
        "display_name": "Data Engineer",
        "kra_matches": [
          {
            "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": "Experience/ knowledge in big data using Scala spark, ML, Kafka, Elastic search will be plus.",
            "similarity": 0.5643
          },
          {
            "kra_text": "Works with data analysts, data scientists, and business stakeholders to define data models, ingestion schedules, and data delivery requirements.",
            "sentence": "5/6 to 8/9 years with 2+ Years of relevant Experience in Big data",
            "similarity": 0.4505
          },
          {
            "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": "Should have tool development using Python or Scala.",
            "similarity": 0.4301
          }
        ],
        "matched_count": null,
        "matched_skills": null,
        "role_id": 2,
        "score": 0.4816,
        "slug": "data-engineer",
        "total_count": null
      },
      {
        "display_name": "Fullstack Developer",
        "kra_matches": [
          {
            "kra_text": "Implements complete product features end-to-end from database schema design through backend API to frontend UI using JavaScript, TypeScript, Python, or Ruby on Rails.",
            "sentence": "Should have tool development using Python or Scala.",
            "similarity": 0.4104
          },
          {
            "kra_text": "Works closely with product managers and UX designers to translate requirements and wireframes into working software features through iterative development.",
            "sentence": "Should have worked in product companies only.",
            "similarity": 0.3793
          },
          {
            "kra_text": "Designs and queries relational databases like PostgreSQL and document stores like MongoDB, writing migrations, indexes, and optimized queries.",
            "sentence": "Most importantly should be strong in Data Structures and Algorithms.",
            "similarity": 0.3756
          }
        ],
        "matched_count": null,
        "matched_skills": null,
        "role_id": 15,
        "score": 0.3884,
        "slug": "full-stack-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": "5/6 to 8/9 years with 2+ Years of relevant Experience in Big data",
            "similarity": 0.3793
          },
          {
            "kra_text": "Prepares, cleans, and transforms training datasets, manages feature stores, and builds feature engineering pipelines for model training.",
            "sentence": "Experience/ knowledge in big data using Scala spark, ML, Kafka, Elastic search will be plus.",
            "similarity": 0.3743
          },
          {
            "kra_text": "Designs end-to-end ML training pipelines and model inference workflows using TensorFlow, PyTorch, or scikit-learn on cloud ML platforms.",
            "sentence": "Should have tool development using Python or Scala.",
            "similarity": 0.3505
          }
        ],
        "matched_count": null,
        "matched_skills": null,
        "role_id": 3,
        "score": 0.368,
        "slug": "ml-engineer",
        "total_count": null
      },
      {
        "display_name": "Java Backend Developer",
        "kra_matches": [
          {
            "kra_text": "persistence and data modeling",
            "sentence": "Most importantly should be strong in Data Structures and Algorithms.",
            "similarity": 0.3798
          },
          {
            "kra_text": "persistence and data modeling",
            "sentence": "5/6 to 8/9 years with 2+ Years of relevant Experience in Big data",
            "similarity": 0.365
          },
          {
            "kra_text": "service endpoint development",
            "sentence": "Should have tool development using Python or Scala.",
            "similarity": 0.3404
          }
        ],
        "matched_count": null,
        "matched_skills": null,
        "role_id": 79,
        "score": 0.3618,
        "slug": "java-backend-developer",
        "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": "Should have tool development using Python or Scala.",
            "similarity": 0.4078
          },
          {
            "kra_text": "Designs and implements prompt engineering workflows, few-shot examples, chain-of-thought patterns, and structured output parsing for AI feature pipelines.",
            "sentence": "Expertise with functional programming using Scala",
            "similarity": 0.3351
          },
          {
            "kra_text": "Designs and implements prompt engineering workflows, few-shot examples, chain-of-thought patterns, and structured output parsing for AI feature pipelines.",
            "sentence": "Experience/ knowledge in big data using Scala spark, ML, Kafka, Elastic search will be plus.",
            "similarity": 0.3232
          }
        ],
        "matched_count": null,
        "matched_skills": null,
        "role_id": 13,
        "score": 0.3554,
        "slug": "ai-engineer",
        "total_count": null
      }
    ],
    "skill_match_roles": [
      {
        "display_name": "Backend Developer",
        "kra_matches": null,
        "matched_count": 3,
        "matched_skills": [
          "NoSQL",
          "REST",
          "microservices"
        ],
        "role_id": 1,
        "score": 0.3333,
        "slug": "backend-engineer",
        "total_count": 9
      },
      {
        "display_name": "ML Engineer",
        "kra_matches": null,
        "matched_count": 2,
        "matched_skills": [
          "Machine Learning",
          "Scala"
        ],
        "role_id": 3,
        "score": 0.2222,
        "slug": "ml-engineer",
        "total_count": 9
      },
      {
        "display_name": "MLOps Engineer",
        "kra_matches": null,
        "matched_count": 2,
        "matched_skills": [
          "Machine Learning",
          "Scala"
        ],
        "role_id": 16,
        "score": 0.2222,
        "slug": "ml-ops-engineer",
        "total_count": 9
      },
      {
        "display_name": "Data Engineer",
        "kra_matches": null,
        "matched_count": 2,
        "matched_skills": [
          "SQL",
          "Scala"
        ],
        "role_id": 2,
        "score": 0.2222,
        "slug": "data-engineer",
        "total_count": 9
      },
      {
        "display_name": "Pega Developer",
        "kra_matches": null,
        "matched_count": 2,
        "matched_skills": [
          "REST",
          "SQL"
        ],
        "role_id": 24,
        "score": 0.2222,
        "slug": "pega-developer",
        "total_count": 9
      }
    ]
  },
  "stage4_decision": {
    "alias_collision_detected": false,
    "case": "DOMAIN",
    "chosen_role": {
      "display_name": "Data Engineer",
      "kra_matches": null,
      "matched_count": null,
      "matched_skills": null,
      "role_id": 2,
      "score": 0.95,
      "slug": "data-engineer",
      "total_count": null
    },
    "confidence": 0.95,
    "is_new_role": false,
    "llm2_fired": false,
    "llm2_reasoning": null,
    "matched_dimensions": [
      "Microservices Development",
      "Big Data Engineering",
      "RESTful API Development",
      "Programming Language Proficiency",
      "Search and Machine Learning Integration",
      "Algorithmic Problem Solving"
    ],
    "matched_kras": [
      "building modern and scalable REST-based microservices",
      "implementing RESTful web services in Scala, Java or similar languages",
      "experience with No SQL and SQL databases",
      "experience in information retrieval and machine learning",
      "tool development using Python or Scala"
    ],
    "matched_skills": [
      "Scala",
      "Play",
      "REST",
      "functional programming",
      "SQL",
      "No SQL",
      "machine learning",
      "Scala spark",
      "Kafka",
      "Elastic search",
      "Python",
      "Data Structures and Algorithms"
    ],
    "new_role_display_name": null,
    "new_role_slug": null,
    "queued": false,
    "reasoning": "Domain=Data Engineering \u0026 Analytics; The JD is centered on Scala-based microservices, big data tooling, Kafka/Spark/ElasticSearch, and tool development, which best matches a Data Engineer profile rather than analytics or warehouse-specific roles.",
    "sub_role": null
  },
  "stage5_updates": {
    "centroid_n_after": 58,
    "centroid_updated": true,
    "collision_log_id": null,
    "new_kra_attached": null,
    "new_skills_attached": [
      {
        "is_primary": false,
        "queue_id": 3844,
        "role_display_name": "Data Engineer",
        "role_slug": "data-engineer",
        "skill_name": "Play",
        "status": "pending"
      },
      {
        "is_primary": true,
        "queue_id": 3845,
        "role_display_name": "Data Engineer",
        "role_slug": "data-engineer",
        "skill_name": "Functional Programming",
        "status": "pending"
      },
      {
        "is_primary": false,
        "queue_id": 3846,
        "role_display_name": "Data Engineer",
        "role_slug": "data-engineer",
        "skill_name": "ML",
        "status": "pending"
      },
      {
        "is_primary": true,
        "queue_id": 3847,
        "role_display_name": "Data Engineer",
        "role_slug": "data-engineer",
        "skill_name": "Big Data",
        "status": "pending"
      },
      {
        "is_primary": true,
        "queue_id": 3848,
        "role_display_name": "Data Engineer",
        "role_slug": "data-engineer",
        "skill_name": "Data Structures and Algorithms",
        "status": "pending"
      }
    ],
    "queue_entry_id": null,
    "v3_pipeline_triggered": false,
    "v3_role_slug": null,
    "v3_run_id": null
  }
}
API 2 — extract-details
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      "alias_persist_skipped_reason": "alias_text already exists for this canonical skill",
      "alias_persisted": false,
      "existing_alias_id": 106,
      "existing_alias_text": "REST",
      "input_term": "REST",
      "matched_canonical": {
        "category_id": 2,
        "display_name": "REST",
        "id": 11,
        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "CONCEPT",
        "slug": "rest",
        "sub_category_id": 2122,
        "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": 178,
      "existing_alias_text": "microservices",
      "input_term": "Microservices",
      "matched_canonical": {
        "category_id": 1,
        "display_name": "microservices",
        "id": 41,
        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "PATTERN",
        "slug": "microservices",
        "sub_category_id": 1,
        "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": 831,
      "existing_alias_text": "MVC",
      "input_term": "MVC",
      "matched_canonical": {
        "category_id": 1,
        "display_name": "MVC",
        "id": 505,
        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "PATTERN",
        "slug": "mvc",
        "sub_category_id": 2462,
        "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": 1989,
      "existing_alias_text": "NoSQL",
      "input_term": "NoSQL",
      "matched_canonical": {
        "category_id": 2,
        "display_name": "NoSQL",
        "id": 1346,
        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "CONCEPT",
        "slug": "nosql",
        "sub_category_id": 1019,
        "typical_lifespan": "EVERGREEN",
        "volatility": "STABLE"
      },
      "matched_via": "alias"
    },
    {
      "alias_persist_skipped_reason": "alias_text already exists for this canonical skill",
      "alias_persisted": false,
      "existing_alias_id": 271,
      "existing_alias_text": "SQL",
      "input_term": "SQL",
      "matched_canonical": {
        "category_id": 6,
        "display_name": "SQL",
        "id": 101,
        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "LANGUAGE",
        "slug": "sql",
        "sub_category_id": 97,
        "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"
    },
    {
      "alias_persist_skipped_reason": "alias_text already exists for this canonical skill",
      "alias_persisted": false,
      "existing_alias_id": 2004,
      "existing_alias_text": "Apache Spark",
      "input_term": "Apache 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": 173,
      "existing_alias_text": "Kafka",
      "input_term": "Kafka",
      "matched_canonical": {
        "category_id": 3,
        "display_name": "Kafka",
        "id": 36,
        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "TOOL",
        "slug": "kafka",
        "sub_category_id": 3533,
        "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": 4648,
      "existing_alias_text": "Elasticsearch",
      "input_term": "Elasticsearch",
      "matched_canonical": {
        "category_id": 3,
        "display_name": "Elasticsearch",
        "id": 3171,
        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "TOOL",
        "slug": "elasticsearch",
        "sub_category_id": 2925,
        "typical_lifespan": "EVERGREEN",
        "volatility": "STABLE"
      },
      "matched_via": "alias"
    },
    {
      "alias_persist_skipped_reason": "alias_text already exists for this canonical skill",
      "alias_persisted": false,
      "existing_alias_id": 67,
      "existing_alias_text": "Python",
      "input_term": "Python",
      "matched_canonical": {
        "category_id": 6,
        "display_name": "Python",
        "id": 5,
        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "LANGUAGE",
        "slug": "python",
        "sub_category_id": 96,
        "typical_lifespan": "EVERGREEN",
        "volatility": "STABLE"
      },
      "matched_via": "alias"
    },
    {
      "alias_persist_skipped_reason": "TODO: REMOVE AFTER TESTING \u2014 alias DB write disabled",
      "alias_persisted": false,
      "existing_alias_id": 1614,
      "existing_alias_text": "Data Structures",
      "input_term": "Data Structures and Algorithms",
      "matched_canonical": {
        "category_id": 2,
        "display_name": "Data Structures",
        "id": 1003,
        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "CONCEPT",
        "slug": "data-structures",
        "sub_category_id": 731,
        "typical_lifespan": "EVERGREEN",
        "volatility": "STABLE"
      },
      "matched_via": "embedding_alias"
    }
  ],
  "candidate_roles": [
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      "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"
    },
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      "display_name": "Fullstack Developer",
      "id": 15,
      "rationale": null,
      "role_archetype": null,
      "slug": "full-stack-engineer",
      "source": "db"
    },
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      "id": 83,
      "rationale": null,
      "role_archetype": "Engineering",
      "slug": "dotnet-backend-developer",
      "source": "db"
    },
    {
      "display_name": "Go Backend Developer",
      "id": 81,
      "rationale": null,
      "role_archetype": "Engineering",
      "slug": "go-backend-developer",
      "source": "db"
    },
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      "display_name": "Kotlin Backend Developer",
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      "rationale": null,
      "role_archetype": "Engineering",
      "slug": "kotlin-server-backend-developer",
      "source": "db"
    },
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      "rationale": null,
      "role_archetype": "Engineering",
      "slug": "node-backend-developer",
      "source": "db"
    },
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      "display_name": "PHP Backend Developer",
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      "rationale": null,
      "role_archetype": "Engineering",
      "slug": "php-backend-developer",
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    },
    {
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      "rationale": null,
      "role_archetype": "Engineering",
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    },
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      "display_name": "Ruby Backend Developer",
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      "rationale": null,
      "role_archetype": "Engineering",
      "slug": "ruby-backend-developer",
      "source": "db"
    },
    {
      "display_name": "Scala Backend Developer",
      "id": 87,
      "rationale": null,
      "role_archetype": "Engineering",
      "slug": "scala-backend-developer",
      "source": "db"
    },
    {
      "display_name": "Pega Developer",
      "id": 24,
      "rationale": null,
      "role_archetype": null,
      "slug": "pega-developer",
      "source": "db"
    },
    {
      "display_name": "Sitecore Dev",
      "id": 233,
      "rationale": null,
      "role_archetype": "Engineering",
      "slug": "sitecore-dev",
      "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",
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      "rationale": null,
      "role_archetype": null,
      "slug": "ml-ops-engineer",
      "source": "db"
    },
    {
      "display_name": "Android Developer",
      "id": 4,
      "rationale": null,
      "role_archetype": null,
      "slug": "android-engineer",
      "source": "db"
    },
    {
      "display_name": "iOS Developer",
      "id": 6,
      "rationale": null,
      "role_archetype": null,
      "slug": "ios-engineer",
      "source": "db"
    },
    {
      "display_name": "Native Mobile Developer",
      "id": 75,
      "rationale": null,
      "role_archetype": "Engineering",
      "slug": "native-mobile-developer",
      "source": "db"
    },
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      "display_name": "Java Backend Developer",
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      "rationale": null,
      "role_archetype": "Engineering",
      "slug": "java-backend-developer",
      "source": "db"
    },
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      "display_name": "AI Engineer",
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      "rationale": null,
      "role_archetype": null,
      "slug": "ai-engineer",
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    },
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      "display_name": "Magento Dev",
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      "rationale": null,
      "role_archetype": "Engineering",
      "slug": "magento-dev",
      "source": "db"
    },
    {
      "display_name": "Drupal Dev",
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      "rationale": null,
      "role_archetype": "Engineering",
      "slug": "drupal-dev",
      "source": "db"
    },
    {
      "display_name": "Cloud Security Engineer",
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      "rationale": null,
      "role_archetype": null,
      "slug": "cloud-security-engineer",
      "source": "db"
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      "display_name": "Cyber Security Engineer",
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      "slug": "cybersecurity-engineer",
      "source": "db"
    },
    {
      "display_name": "AR/VR Engineer",
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      "slug": "ar-vr-engineer",
      "source": "db"
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  ],
  "chosen_role": {
    "display_name": "Data Engineer",
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    "rationale": "Domain=Data Engineering \u0026 Analytics; The JD is centered on Scala-based microservices, big data tooling, Kafka/Spark/ElasticSearch, and tool development, which best matches a Data Engineer profile rather than analytics or warehouse-specific roles.",
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    "slug": "data-engineer",
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  "dimensions": [
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      },
      "input_skill": "REST",
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      ]
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
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        "rationale": "Designing backend service interfaces and contracts that other systems consume, including endpoint and operation shape, request/response payloads, schema and validation, pagination, filtering, idempotency, versioning, status codes, and backward compatibility across REST, GraphQL, gRPC, and OpenAPI-based APIs.",
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          "display_name": ".NET Backend Developer",
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          "rationale": null,
          "role_archetype": "Engineering",
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          "source": "db"
        },
        {
          "display_name": "Go Backend Developer",
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          "rationale": null,
          "role_archetype": "Engineering",
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          "source": "db"
        },
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          "display_name": "Kotlin Backend Developer",
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          "rationale": null,
          "role_archetype": "Engineering",
          "slug": "kotlin-server-backend-developer",
          "source": "db"
        },
        {
          "display_name": "Node.js Backend Developer",
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          "rationale": null,
          "role_archetype": "Engineering",
          "slug": "node-backend-developer",
          "source": "db"
        },
        {
          "display_name": "PHP Backend Developer",
          "id": 86,
          "rationale": null,
          "role_archetype": "Engineering",
          "slug": "php-backend-developer",
          "source": "db"
        },
        {
          "display_name": "Python Backend Developer",
          "id": 80,
          "rationale": null,
          "role_archetype": "Engineering",
          "slug": "python-backend-developer",
          "source": "db"
        },
        {
          "display_name": "Ruby Backend Developer",
          "id": 85,
          "rationale": null,
          "role_archetype": "Engineering",
          "slug": "ruby-backend-developer",
          "source": "db"
        },
        {
          "display_name": "Scala Backend Developer",
          "id": 87,
          "rationale": null,
          "role_archetype": "Engineering",
          "slug": "scala-backend-developer",
          "source": "db"
        }
      ]
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "Integration Protocols \u0026 Standards",
        "id": 271,
        "rationale": "Standards and protocols for integrating Pega applications.",
        "slug": "integration-protocols-standards",
        "source": "db"
      },
      "input_skill": "REST",
      "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": "Standards \u0026 Protocols Compliance",
        "id": 452,
        "rationale": "Encompasses key web and data standards, protocols, and compliance requirements relevant to Sitecore implementations.",
        "slug": "standards-protocols-compliance",
        "source": "db"
      },
      "input_skill": "REST",
      "llm_role": null,
      "roles_from_db": [
        {
          "display_name": "Sitecore Dev",
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          "rationale": null,
          "role_archetype": "Engineering",
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        }
      ]
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "Microservices and Distributed Systems",
        "id": 9,
        "rationale": "Architectural patterns for decomposed backend systems and the operational concerns they introduce. Covers service boundaries, consistency tradeoffs, retries, circuit breakers, and distributed coordination.",
        "slug": "microservices-and-distributed-systems",
        "source": "db"
      },
      "input_skill": "Microservices",
      "llm_role": null,
      "roles_from_db": [
        {
          "display_name": "Backend Developer",
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          "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",
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        },
        {
          "display_name": "Node.js Backend Developer",
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          "rationale": null,
          "role_archetype": "Engineering",
          "slug": "node-backend-developer",
          "source": "db"
        },
        {
          "display_name": "Scala Backend Developer",
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          "rationale": null,
          "role_archetype": "Engineering",
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          "source": "db"
        }
      ]
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
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        "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",
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          "rationale": null,
          "role_archetype": null,
          "slug": "data-engineer",
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        }
      ]
    },
    {
      "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",
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          "rationale": null,
          "role_archetype": null,
          "slug": "ml-engineer",
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        },
        {
          "display_name": "MLOps Engineer",
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          "rationale": null,
          "role_archetype": null,
          "slug": "ml-ops-engineer",
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      ]
    },
    {
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        "difficulty_hint": "well_known",
        "display_name": "ASP.NET Core Web Frameworks",
        "id": 363,
        "rationale": "Server-side web frameworks and hosting models used to build HTTP APIs, middleware, filters, and request pipelines. This cluster is coherent because it defines how backend services receive, process, and return requests.",
        "slug": "asp-net-core-web-frameworks",
        "source": "db"
      },
      "input_skill": "MVC",
      "llm_role": null,
      "roles_from_db": [
        {
          "display_name": ".NET Backend Developer",
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          "rationale": null,
          "role_archetype": "Engineering",
          "slug": "dotnet-backend-developer",
          "source": "db"
        }
      ]
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "App Architecture and Dependency Injection",
        "id": 94,
        "rationale": "Structural patterns used to organize iOS code into testable, maintainable feature modules and layers. iOS engineers use these patterns to separate UI, state, and service integration concerns.",
        "slug": "app-architecture-and-dependency-injection",
        "source": "db"
      },
      "input_skill": "MVC",
      "llm_role": null,
      "roles_from_db": [
        {
          "display_name": "Android Developer",
          "id": 4,
          "rationale": null,
          "role_archetype": null,
          "slug": "android-engineer",
          "source": "db"
        },
        {
          "display_name": "iOS Developer",
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          "rationale": null,
          "role_archetype": null,
          "slug": "ios-engineer",
          "source": "db"
        }
      ]
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "Application Architecture and Code Organization",
        "id": 220,
        "rationale": "Structural patterns for organizing product code into maintainable modules, layers, and feature boundaries. Full stack engineers need this to keep cross-layer feature work understandable as the product grows.",
        "slug": "application-architecture-and-code-organization",
        "source": "db"
      },
      "input_skill": "MVC",
      "llm_role": null,
      "roles_from_db": [
        {
          "display_name": "Fullstack Developer",
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          "rationale": null,
          "role_archetype": null,
          "slug": "full-stack-engineer",
          "source": "db"
        }
      ]
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "Native Mobile App Architecture and Dependency Injection",
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        "rationale": "Structural patterns for organizing native mobile application code into maintainable, testable modules, layers, and feature boundaries. This includes app architecture patterns such as MVVM, MVC, MVI, VIPER, and Clean Architecture; dependency injection frameworks and patterns such as Hilt, Dagger, and Koin; and code organization techniques such as modularization, feature modules, repository pattern, and use-case layering to separate UI, state, data, and platform concerns across a growing codebase.",
        "slug": "native-mobile-app-architecture-and-dependency-injection",
        "source": "db"
      },
      "input_skill": "MVC",
      "llm_role": null,
      "roles_from_db": [
        {
          "display_name": "Native Mobile Developer",
          "id": 75,
          "rationale": null,
          "role_archetype": "Engineering",
          "slug": "native-mobile-developer",
          "source": "db"
        }
      ]
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "Java Language and JVM",
        "id": 279,
        "rationale": "Core Java implementation skills used to build backend service logic, utilities, and internal abstractions. This is the primary coding surface for the role and includes language features plus JVM behavior that affect correctness and maintainability.",
        "slug": "java-language-and-jvm",
        "source": "db"
      },
      "input_skill": "Java",
      "llm_role": null,
      "roles_from_db": [
        {
          "display_name": "Java Backend Developer",
          "id": 79,
          "rationale": null,
          "role_archetype": "Engineering",
          "slug": "java-backend-developer",
          "source": "db"
        },
        {
          "display_name": "Kotlin Backend Developer",
          "id": 84,
          "rationale": null,
          "role_archetype": "Engineering",
          "slug": "kotlin-server-backend-developer",
          "source": "db"
        },
        {
          "display_name": "Scala Backend Developer",
          "id": 87,
          "rationale": null,
          "role_archetype": "Engineering",
          "slug": "scala-backend-developer",
          "source": "db"
        }
      ]
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "Kotlin and Java",
        "id": 161,
        "rationale": "Primary implementation languages for Android app features, platform integration, and client-side business logic. Android engineers use these languages to build screens, state flows, service adapters, and device-aware behavior.",
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        "source": "db"
      },
      "input_skill": "Java",
      "llm_role": null,
      "roles_from_db": [
        {
          "display_name": "Android Developer",
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          "rationale": null,
          "role_archetype": null,
          "slug": "android-engineer",
          "source": "db"
        }
      ]
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "Native Mobile Languages",
        "id": 274,
        "rationale": "Primary implementation languages used to build platform-specific app features, UI logic, and device integrations. This is the core coding surface for native mobile work on one platform.",
        "slug": "native-mobile-languages",
        "source": "db"
      },
      "input_skill": "Java",
      "llm_role": null,
      "roles_from_db": [
        {
          "display_name": "Native Mobile Developer",
          "id": 75,
          "rationale": null,
          "role_archetype": "Engineering",
          "slug": "native-mobile-developer",
          "source": "db"
        }
      ]
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "Pega Programming Languages \u0026 DSLs",
        "id": 267,
        "rationale": "Programming languages and domain-specific languages used in Pega development.",
        "slug": "pega-programming-languages-dsls",
        "source": "db"
      },
      "input_skill": "Java",
      "llm_role": null,
      "roles_from_db": [
        {
          "display_name": "Pega Developer",
          "id": 24,
          "rationale": null,
          "role_archetype": null,
          "slug": "pega-developer",
          "source": "db"
        }
      ]
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "Programming Languages",
        "id": 1,
        "rationale": "Primary implementation languages used to build client and server feature code. Full stack engineers need enough fluency to move across layers and implement product behavior end to end.",
        "slug": "programming-languages",
        "source": "db"
      },
      "input_skill": "Java",
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      "roles_from_db": [
        {
          "display_name": "Backend Developer",
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          "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",
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        },
        {
          "display_name": "Fullstack Developer",
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          "rationale": null,
          "role_archetype": null,
          "slug": "full-stack-engineer",
          "source": "db"
        }
      ]
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "Programming Languages for Data Work",
        "id": 21,
        "rationale": "Languages used to implement data pipelines, transformations, and operational glue. This is the primary coding surface for building ingestion, enrichment, and automation logic in data engineering.",
        "slug": "programming-languages-for-data-work",
        "source": "db"
      },
      "input_skill": "Java",
      "llm_role": null,
      "roles_from_db": [
        {
          "display_name": "Data Engineer",
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          "rationale": null,
          "role_archetype": null,
          "slug": "data-engineer",
          "source": "db"
        }
      ]
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "NoSQL Databases",
        "id": 19,
        "rationale": "Models and manages data using non-relational database systems.",
        "slug": "nosql-databases",
        "source": "db"
      },
      "input_skill": "NoSQL",
      "llm_role": null,
      "roles_from_db": [
        {
          "display_name": "Backend Developer",
          "id": 1,
          "rationale": null,
          "role_archetype": "A Backend Engineer designs, builds, and maintains the server-side logic and data handling that power applications and services. They focus on implementing reliable business functionality, integrating with other systems, and ensuring the backend is scalable, maintainable, and observable.",
          "slug": "backend-engineer",
          "source": "db"
        }
      ]
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "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": "SQL",
      "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 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": "SQL",
      "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": "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",
          "id": 13,
          "rationale": null,
          "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",
          "id": 16,
          "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",
      "llm_role": null,
      "roles_from_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": "Apache Spark",
      "llm_role": null,
      "roles_from_db": [
        {
          "display_name": "Data Engineer",
          "id": 2,
          "rationale": null,
          "role_archetype": null,
          "slug": "data-engineer",
          "source": "db"
        }
      ]
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "Asynchronous Messaging and Event Streaming",
        "id": 297,
        "rationale": "Asynchronous communication patterns and broker technologies used to decouple backend services and move work off the request path. Includes queues, pub/sub, event streams, consumer groups, dead-letter queues, and delivery semantics across systems such as Kafka, RabbitMQ, NATS, SQS/SNS, Pulsar, and ActiveMQ.",
        "slug": "asynchronous-messaging-and-event-streaming",
        "source": "db"
      },
      "input_skill": "Kafka",
      "llm_role": null,
      "roles_from_db": [
        {
          "display_name": ".NET Backend Developer",
          "id": 83,
          "rationale": null,
          "role_archetype": "Engineering",
          "slug": "dotnet-backend-developer",
          "source": "db"
        },
        {
          "display_name": "Go Backend Developer",
          "id": 81,
          "rationale": null,
          "role_archetype": "Engineering",
          "slug": "go-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": "Node.js Backend Developer",
          "id": 82,
          "rationale": null,
          "role_archetype": "Engineering",
          "slug": "node-backend-developer",
          "source": "db"
        },
        {
          "display_name": "Scala Backend Developer",
          "id": 87,
          "rationale": null,
          "role_archetype": "Engineering",
          "slug": "scala-backend-developer",
          "source": "db"
        }
      ]
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "Messaging and Background Jobs",
        "id": 291,
        "rationale": "Asynchronous processing patterns and worker systems used to decouple backend work from request handling. This is a coherent cluster because the role supports background jobs, retries, and deferred processing.",
        "slug": "messaging-and-background-jobs",
        "source": "db"
      },
      "input_skill": "Kafka",
      "llm_role": null,
      "roles_from_db": [
        {
          "display_name": "PHP Backend Developer",
          "id": 86,
          "rationale": null,
          "role_archetype": "Engineering",
          "slug": "php-backend-developer",
          "source": "db"
        },
        {
          "display_name": "Python Backend Developer",
          "id": 80,
          "rationale": null,
          "role_archetype": "Engineering",
          "slug": "python-backend-developer",
          "source": "db"
        },
        {
          "display_name": "Ruby Backend Developer",
          "id": 85,
          "rationale": null,
          "role_archetype": "Engineering",
          "slug": "ruby-backend-developer",
          "source": "db"
        }
      ]
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "Messaging and Event Streaming",
        "id": 8,
        "rationale": "Transport-layer systems used to move events and decouple producers from consumers. Data engineers use these systems to ingest, buffer, and distribute event data before downstream processing.",
        "slug": "messaging-and-event-streaming",
        "source": "db"
      },
      "input_skill": "Kafka",
      "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": "Data Engineer",
          "id": 2,
          "rationale": null,
          "role_archetype": null,
          "slug": "data-engineer",
          "source": "db"
        }
      ]
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "Magento Search and Indexing",
        "id": 403,
        "rationale": "Index-driven storefront data freshness and search behavior. This cluster is coherent because Magento commerce sites depend on indexing to keep catalog, price, and search results aligned with changing data.",
        "slug": "magento-search-and-indexing",
        "source": "db"
      },
      "input_skill": "Elasticsearch",
      "llm_role": null,
      "roles_from_db": [
        {
          "display_name": "Magento Dev",
          "id": 231,
          "rationale": null,
          "role_archetype": "Engineering",
          "slug": "magento-dev",
          "source": "db"
        }
      ]
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "Search and Content Discovery",
        "id": 356,
        "rationale": "Implementing site search, indexing, and content discovery features in Drupal. This cluster is coherent because many Drupal sites need structured search experiences beyond basic navigation.",
        "slug": "search-and-content-discovery",
        "source": "db"
      },
      "input_skill": "Elasticsearch",
      "llm_role": null,
      "roles_from_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"
        }
      ]
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "Cloud Security Scripting \u0026 DSL Languages",
        "id": 248,
        "rationale": "Proficiency in programming and domain-specific languages used to automate and script cloud security controls.",
        "slug": "cloud-security-scripting-dsl-languages",
        "source": "db"
      },
      "input_skill": "Python",
      "llm_role": null,
      "roles_from_db": [
        {
          "display_name": "Cloud Security Engineer",
          "id": 23,
          "rationale": null,
          "role_archetype": null,
          "slug": "cloud-security-engineer",
          "source": "db"
        }
      ]
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "Programming Languages",
        "id": 1,
        "rationale": "Primary implementation languages used to build client and server feature code. Full stack engineers need enough fluency to move across layers and implement product behavior end to end.",
        "slug": "programming-languages",
        "source": "db"
      },
      "input_skill": "Python",
      "llm_role": null,
      "roles_from_db": [
        {
          "display_name": "Backend Developer",
          "id": 1,
          "rationale": null,
          "role_archetype": "A Backend Engineer designs, builds, and maintains the server-side logic and data handling that power applications and services. They focus on implementing reliable business functionality, integrating with other systems, and ensuring the backend is scalable, maintainable, and observable.",
          "slug": "backend-engineer",
          "source": "db"
        },
        {
          "display_name": "Fullstack Developer",
          "id": 15,
          "rationale": null,
          "role_archetype": null,
          "slug": "full-stack-engineer",
          "source": "db"
        }
      ]
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "Programming Languages and Scripting",
        "id": 59,
        "rationale": "Languages used to write security automation, analysis scripts, detection logic, and remediation helpers. This is the primary implementation surface for a cybersecurity engineer across tooling and response workflows.",
        "slug": "programming-languages-and-scripting",
        "source": "db"
      },
      "input_skill": "Python",
      "llm_role": null,
      "roles_from_db": [
        {
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            "slug": "programming-languages-and-scripting",
            "source": "db"
          },
          "input_skill": "Python",
          "llm_role": null,
          "roles_from_db": [
            {
              "display_name": "Cyber Security Engineer",
              "id": 5,
              "rationale": null,
              "role_archetype": null,
              "slug": "cybersecurity-engineer",
              "source": "db"
            }
          ]
        },
        {
          "dimension": {
            "difficulty_hint": "well_known",
            "display_name": "Programming Languages for Data Work",
            "id": 21,
            "rationale": "Languages used to implement data pipelines, transformations, and operational glue. This is the primary coding surface for building ingestion, enrichment, and automation logic in data engineering.",
            "slug": "programming-languages-for-data-work",
            "source": "db"
          },
          "input_skill": "Python",
          "llm_role": null,
          "roles_from_db": [
            {
              "display_name": "Data Engineer",
              "id": 2,
              "rationale": null,
              "role_archetype": null,
              "slug": "data-engineer",
              "source": "db"
            }
          ]
        },
        {
          "dimension": {
            "difficulty_hint": "well_known",
            "display_name": "Programming Languages for ML Systems",
            "id": 39,
            "rationale": "Languages used to build training code, inference services, evaluation jobs, and ML glue code. This is the primary implementation surface for ML engineers across experimentation and productionization.",
            "slug": "programming-languages-for-ml-systems",
            "source": "db"
          },
          "input_skill": "Python",
          "llm_role": null,
          "roles_from_db": [
            {
              "display_name": "ML Engineer",
              "id": 3,
              "rationale": null,
              "role_archetype": null,
              "slug": "ml-engineer",
              "source": "db"
            },
            {
              "display_name": "MLOps Engineer",
              "id": 16,
              "rationale": null,
              "role_archetype": null,
              "slug": "ml-ops-engineer",
              "source": "db"
            }
          ]
        },
        {
          "dimension": {
            "difficulty_hint": "well_known",
            "display_name": "Programming Languages for XR",
            "id": 97,
            "rationale": "Primary implementation languages used to build immersive client features, interaction logic, and device-specific runtime behavior. This is the core coding surface for AR/VR experiences.",
            "slug": "programming-languages-for-xr",
            "source": "db"
          },
          "input_skill": "Python",
          "llm_role": null,
          "roles_from_db": [
            {
              "display_name": "AR/VR Engineer",
              "id": 8,
              "rationale": null,
              "role_archetype": null,
              "slug": "ar-vr-engineer",
              "source": "db"
            }
          ]
        },
        {
          "dimension": {
            "difficulty_hint": "well_known",
            "display_name": "Python Programming",
            "id": 290,
            "rationale": "Core Python language skills used to implement backend business logic, request handlers, integrations, and service internals. This is the primary coding surface for the role.",
            "slug": "python-programming",
            "source": "db"
          },
          "input_skill": "Python",
          "llm_role": null,
          "roles_from_db": [
            {
              "display_name": "Python Backend Developer",
              "id": 80,
              "rationale": null,
              "role_archetype": "Engineering",
              "slug": "python-backend-developer",
              "source": "db"
            }
          ]
        }
      ],
      "input_skill": "Python",
      "matched_via": "alias",
      "new_alias_persisted": false,
      "new_alias_text": null,
      "new_skill_meta": null,
      "source_tag": "db",
      "was_in_llm_skills": true
    },
    {
      "aliases_in_db": [
        {
          "alias_text": "Data Structures",
          "alias_type": "CANONICAL",
          "id": 1614,
          "is_primary": false,
          "match_strategy": "CASE_INSENSITIVE"
        }
      ],
      "canonical": {
        "category_id": 2,
        "display_name": "Data Structures",
        "id": 1003,
        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "CONCEPT",
        "slug": "data-structures",
        "sub_category_id": 731,
        "typical_lifespan": "EVERGREEN",
        "volatility": "STABLE"
      },
      "dimensions": [
        {
          "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": "Data Structures and Algorithms",
          "llm_role": null,
          "roles_from_db": []
        }
      ],
      "input_skill": "Data Structures and Algorithms",
      "matched_via": "embedding_alias",
      "new_alias_persisted": false,
      "new_alias_text": null,
      "new_skill_meta": null,
      "source_tag": "db",
      "was_in_llm_skills": true
    }
  ],
  "unmatched_skills": [
    "Play",
    "Functional Programming",
    "ML",
    "Big Data"
  ]
}
API 3 — final-role-output
{
  "chosen_role": {
    "display_name": "Data Engineer",
    "id": 2,
    "rationale": "Domain=Data Engineering \u0026 Analytics; The JD is centered on Scala-based microservices, big data tooling, Kafka/Spark/ElasticSearch, and tool development, which best matches a Data Engineer profile rather than analytics or warehouse-specific roles.",
    "role_archetype": null,
    "slug": "data-engineer",
    "source": "db"
  },
  "chosen_role_resolution": "in_db",
  "final_input_skills": [
    {
      "skill": "REST",
      "tag": "in_db"
    },
    {
      "skill": "Microservices",
      "tag": "in_db"
    },
    {
      "skill": "Scala",
      "tag": "in_db"
    },
    {
      "skill": "Play",
      "tag": "new"
    },
    {
      "skill": "MVC",
      "tag": "in_db"
    },
    {
      "skill": "Functional Programming",
      "tag": "new"
    },
    {
      "skill": "Java",
      "tag": "in_db"
    },
    {
      "skill": "NoSQL",
      "tag": "in_db"
    },
    {
      "skill": "SQL",
      "tag": "in_db"
    },
    {
      "skill": "Machine Learning",
      "tag": "in_db"
    },
    {
      "skill": "Apache Spark",
      "tag": "in_db"
    },
    {
      "skill": "ML",
      "tag": "new"
    },
    {
      "skill": "Kafka",
      "tag": "in_db"
    },
    {
      "skill": "Elasticsearch",
      "tag": "in_db"
    },
    {
      "skill": "Big Data",
      "tag": "new"
    },
    {
      "skill": "Python",
      "tag": "in_db"
    },
    {
      "skill": "Data Structures and Algorithms",
      "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": "API Design and Contracts",
          "id": 3,
          "rationale": "Designing request/response shapes and the rules that govern client-server interaction. This cluster is coherent because full stack engineers often own the contract between UI behavior and backend implementation.",
          "slug": "api-design-and-contracts",
          "source": "db"
        },
        "dimension_id": 3,
        "input_skill": "REST",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": "Backend Developer",
            "id": 1,
            "rationale": null,
            "role_archetype": "A Backend Engineer designs, builds, and maintains the server-side logic and data handling that power applications and services. They focus on implementing reliable business functionality, integrating with other systems, and ensuring the backend is scalable, maintainable, and observable.",
            "slug": "backend-engineer",
            "source": "db"
          },
          {
            "display_name": "Fullstack Developer",
            "id": 15,
            "rationale": null,
            "role_archetype": null,
            "slug": "full-stack-engineer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 11,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 2,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "API Interface and Contract Design",
          "id": 289,
          "rationale": "Designing backend service interfaces and contracts that other systems consume, including endpoint and operation shape, request/response payloads, schema and validation, pagination, filtering, idempotency, versioning, status codes, and backward compatibility across REST, GraphQL, gRPC, and OpenAPI-based APIs.",
          "slug": "api-interface-and-contract-design",
          "source": "db"
        },
        "dimension_id": 289,
        "input_skill": "REST",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": ".NET Backend Developer",
            "id": 83,
            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "dotnet-backend-developer",
            "source": "db"
          },
          {
            "display_name": "Go Backend Developer",
            "id": 81,
            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "go-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": "Node.js Backend Developer",
            "id": 82,
            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "node-backend-developer",
            "source": "db"
          },
          {
            "display_name": "PHP Backend Developer",
            "id": 86,
            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "php-backend-developer",
            "source": "db"
          },
          {
            "display_name": "Python Backend Developer",
            "id": 80,
            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "python-backend-developer",
            "source": "db"
          },
          {
            "display_name": "Ruby Backend Developer",
            "id": 85,
            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "ruby-backend-developer",
            "source": "db"
          },
          {
            "display_name": "Scala Backend Developer",
            "id": 87,
            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "scala-backend-developer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 11,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 2,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Integration Protocols \u0026 Standards",
          "id": 271,
          "rationale": "Standards and protocols for integrating Pega applications.",
          "slug": "integration-protocols-standards",
          "source": "db"
        },
        "dimension_id": 271,
        "input_skill": "REST",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": "Pega Developer",
            "id": 24,
            "rationale": null,
            "role_archetype": null,
            "slug": "pega-developer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 11,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 2,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Standards \u0026 Protocols Compliance",
          "id": 452,
          "rationale": "Encompasses key web and data standards, protocols, and compliance requirements relevant to Sitecore implementations.",
          "slug": "standards-protocols-compliance",
          "source": "db"
        },
        "dimension_id": 452,
        "input_skill": "REST",
        "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": "Sitecore Dev",
            "id": 233,
            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "sitecore-dev",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 11,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 2,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Microservices and Distributed Systems",
          "id": 9,
          "rationale": "Architectural patterns for decomposed backend systems and the operational concerns they introduce. Covers service boundaries, consistency tradeoffs, retries, circuit breakers, and distributed coordination.",
          "slug": "microservices-and-distributed-systems",
          "source": "db"
        },
        "dimension_id": 9,
        "input_skill": "Microservices",
        "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": "Node.js Backend Developer",
            "id": 82,
            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "node-backend-developer",
            "source": "db"
          },
          {
            "display_name": "Scala Backend Developer",
            "id": 87,
            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "scala-backend-developer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 41,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 2,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Programming Languages for Data Work",
          "id": 21,
          "rationale": "Languages used to implement data pipelines, transformations, and operational glue. This is the primary coding surface for building ingestion, enrichment, and automation logic in data engineering.",
          "slug": "programming-languages-for-data-work",
          "source": "db"
        },
        "dimension_id": 21,
        "input_skill": "Scala",
        "llm_role": null,
        "matched_chosen_role": true,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension saved",
        "role_dimension_saved": true,
        "roles_from_db": [
          {
            "display_name": "Data Engineer",
            "id": 2,
            "rationale": null,
            "role_archetype": null,
            "slug": "data-engineer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 102,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 2,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Programming Languages for ML Systems",
          "id": 39,
          "rationale": "Languages used to build training code, inference services, evaluation jobs, and ML glue code. This is the primary implementation surface for ML engineers across experimentation and productionization.",
          "slug": "programming-languages-for-ml-systems",
          "source": "db"
        },
        "dimension_id": 39,
        "input_skill": "Scala",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": "ML Engineer",
            "id": 3,
            "rationale": null,
            "role_archetype": null,
            "slug": "ml-engineer",
            "source": "db"
          },
          {
            "display_name": "MLOps Engineer",
            "id": 16,
            "rationale": null,
            "role_archetype": null,
            "slug": "ml-ops-engineer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 102,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 2,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "ASP.NET Core Web Frameworks",
          "id": 363,
          "rationale": "Server-side web frameworks and hosting models used to build HTTP APIs, middleware, filters, and request pipelines. This cluster is coherent because it defines how backend services receive, process, and return requests.",
          "slug": "asp-net-core-web-frameworks",
          "source": "db"
        },
        "dimension_id": 363,
        "input_skill": "MVC",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": ".NET Backend Developer",
            "id": 83,
            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "dotnet-backend-developer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 505,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 2,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "App Architecture and Dependency Injection",
          "id": 94,
          "rationale": "Structural patterns used to organize iOS code into testable, maintainable feature modules and layers. iOS engineers use these patterns to separate UI, state, and service integration concerns.",
          "slug": "app-architecture-and-dependency-injection",
          "source": "db"
        },
        "dimension_id": 94,
        "input_skill": "MVC",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": "Android Developer",
            "id": 4,
            "rationale": null,
            "role_archetype": null,
            "slug": "android-engineer",
            "source": "db"
          },
          {
            "display_name": "iOS Developer",
            "id": 6,
            "rationale": null,
            "role_archetype": null,
            "slug": "ios-engineer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 505,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 2,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Application Architecture and Code Organization",
          "id": 220,
          "rationale": "Structural patterns for organizing product code into maintainable modules, layers, and feature boundaries. Full stack engineers need this to keep cross-layer feature work understandable as the product grows.",
          "slug": "application-architecture-and-code-organization",
          "source": "db"
        },
        "dimension_id": 220,
        "input_skill": "MVC",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": "Fullstack Developer",
            "id": 15,
            "rationale": null,
            "role_archetype": null,
            "slug": "full-stack-engineer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 505,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 2,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Native Mobile App Architecture and Dependency Injection",
          "id": 273,
          "rationale": "Structural patterns for organizing native mobile application code into maintainable, testable modules, layers, and feature boundaries. This includes app architecture patterns such as MVVM, MVC, MVI, VIPER, and Clean Architecture; dependency injection frameworks and patterns such as Hilt, Dagger, and Koin; and code organization techniques such as modularization, feature modules, repository pattern, and use-case layering to separate UI, state, data, and platform concerns across a growing codebase.",
          "slug": "native-mobile-app-architecture-and-dependency-injection",
          "source": "db"
        },
        "dimension_id": 273,
        "input_skill": "MVC",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": "Native Mobile Developer",
            "id": 75,
            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "native-mobile-developer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 505,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 2,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Java Language and JVM",
          "id": 279,
          "rationale": "Core Java implementation skills used to build backend service logic, utilities, and internal abstractions. This is the primary coding surface for the role and includes language features plus JVM behavior that affect correctness and maintainability.",
          "slug": "java-language-and-jvm",
          "source": "db"
        },
        "dimension_id": 279,
        "input_skill": "Java",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": "Java Backend Developer",
            "id": 79,
            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "java-backend-developer",
            "source": "db"
          },
          {
            "display_name": "Kotlin Backend Developer",
            "id": 84,
            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "kotlin-server-backend-developer",
            "source": "db"
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          "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.",
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        "roles_from_db": [
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          "slug": "d_init_01",
          "source": "db"
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        "dimension_id": 96,
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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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        "skill_id": 1356,
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          "source": "db"
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        "input_skill": "Apache Spark",
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        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension saved",
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        "roles_from_db": [
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            "slug": "data-engineer",
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        "skill_dimension_saved": true,
        "skill_id": 1350,
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          "rationale": "Asynchronous communication patterns and broker technologies used to decouple backend services and move work off the request path. Includes queues, pub/sub, event streams, consumer groups, dead-letter queues, and delivery semantics across systems such as Kafka, RabbitMQ, NATS, SQS/SNS, Pulsar, and ActiveMQ.",
          "slug": "asynchronous-messaging-and-event-streaming",
          "source": "db"
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        "dimension_id": 297,
        "input_skill": "Kafka",
        "llm_role": null,
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        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [
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            "display_name": ".NET Backend Developer",
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            "role_archetype": "Engineering",
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            "display_name": "Go Backend Developer",
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            "role_archetype": "Engineering",
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            "source": "db"
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            "display_name": "Kotlin Backend Developer",
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            "role_archetype": "Engineering",
            "slug": "kotlin-server-backend-developer",
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            "display_name": "Node.js Backend Developer",
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            "rationale": null,
            "role_archetype": "Engineering",
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            "display_name": "Scala Backend Developer",
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        "skill_dimension_saved": true,
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        "skipped_reason": null
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          "rationale": "Asynchronous processing patterns and worker systems used to decouple backend work from request handling. This is a coherent cluster because the role supports background jobs, retries, and deferred processing.",
          "slug": "messaging-and-background-jobs",
          "source": "db"
        },
        "dimension_id": 291,
        "input_skill": "Kafka",
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        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [
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            "display_name": "PHP Backend Developer",
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            "display_name": "Python Backend Developer",
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            "display_name": "Ruby Backend Developer",
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        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension saved",
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        },
        "dimension_id": 403,
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        "roles_from_db": [
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          "rationale": "Implementing site search, indexing, and content discovery features in Drupal. This cluster is coherent because many Drupal sites need structured search experiences beyond basic navigation.",
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        "dimension_id": 356,
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        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [
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            "display_name": "Drupal Dev",
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            "rationale": null,
            "role_archetype": "Engineering",
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          {
            "display_name": "Sitecore Dev",
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        "skill_dimension_saved": true,
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          "rationale": "Proficiency in programming and domain-specific languages used to automate and script cloud security controls.",
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        "dimension_id": 248,
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        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [
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            "display_name": "Cloud Security Engineer",
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        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
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            "display_name": "Fullstack Developer",
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          "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.",
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        },
        "dimension_id": 59,
        "input_skill": "Python",
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        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": "Cyber Security Engineer",
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            "rationale": null,
            "role_archetype": null,
            "slug": "cybersecurity-engineer",
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        ],
        "skill_dimension_saved": true,
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          "display_name": "Programming Languages for Data Work",
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        "input_skill": "Python",
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        "matched_chosen_role": true,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension saved",
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          {
            "display_name": "Data Engineer",
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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": "AR/VR Engineer",
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        "input_skill": "Python",
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        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": "Python Backend Developer",
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        ],
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      },
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        },
        "dimension_id": 96,
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        "roles_from_db": [],
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        "skill_id": null,
        "skill_tag": "new",
        "skipped_reason": "skill_not_in_db_v3_proposed"
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    ],
    "new_skills_created": 0,
    "role_dimension_saved": 0,
    "skill_dimension_saved": 0,
    "skipped": 1
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  "planner_output": null,
  "run_id": "13c0eb73-def6-461d-9429-7e9a6d29af3d"
}

LLM Calls

Every model call made for this run, in pipeline order. Click a card to see the model's response.

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