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Pipeline run

ed0f46b3-a688-41c4-b60e-a7f230eb8e50

Pipeline LLM cost (USD)
API 1: $0.0099 API 2: $0.0006 API 3: $0.0000 Total: $0.0106

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 and maintain large-scale web crawlers/scrapers in Python to pull data from multiple sources, clean and format it, extract from PDFs/images/raw docs, expose APIs if needed, and add integrity/monitoring/tests to keep the data reliable.
"Design and implement the data crawling architecture and a large-scale crawling system."
Tech stack maturity
Modern Cloud Native
The skill mix of Docker, microservices, Python, REST, SQL, and unit testing aligns with contemporary cloud-native data engineering practices.
AI index (0 = no AI use, 5 = totally AI-dependent · v2.1)
0.00 / 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):
Evidence — skills matched in JD (27)
Python Shell Scripting SQL Scrapy Beautiful Soup Selenium pandas XPath HTML DOM Requests PDF Git Linux Unix Docker REST Microservices Unit Testing HTTP Proxy SVN Distributed Systems Real-time Systems High Throughput Systems Low Latency Systems Scalability +2
Skill cluster (5 dimension groups, role-scoped)
Programming Languages for Data Work
Python SQL
Cloud Platforms
Distributed Systems
Containerization and Image Builds
Docker
Integration Protocols & Standards
REST
Cross-cutting / unaligned
Shell Scripting Scrapy Beautiful Soup Selenium pandas XPath HTML DOM Requests PDF Git Linux Unix Microservices Unit Testing HTTP Proxy SVN Real-time Systems High Throughput Systems Low Latency Systems Scalability Chrome Developer Tools CAPTCHA
Show KRA description ↓
Above anything else we are looking for a team player who can work harmonically within the team. Design and implement the data crawling architecture and a large-scale crawling system. Develop not just large-scale scraping tools but also data integrity, health, and monitoring systems. Collaborate with data and analytics experts to understand/anticipate requirements and strive for greater functionality in our data gathering system. Should be applied and set to fetch data from multiple online sources, cleanse it, and build APIs on top of it if required. Design, implement and maintain various components of our data infrastructure (Scraping data from Multiple sources and storing it in a formatted manner). Web crawlers/scrapers for a wide variety of alternative datasets. Data extractors for PDF, Images, and various other kinds of raw documents. Third-Party Data Integrations if required. Incrementally improve the quality of our offerings. Author tests to validate data availability and integrity. Recommend and sometimes implement ways to improve data reliability, efficiency, and quality of data gathering processes. Work well in the team with little supervision to research and test innovative solutions. 2+ years of web crawling/ scraping experience is recommended. A solid foundation in computer science, with strong proficiencies in data structures, algorithms, and software design and how they impact the efficiency of the system in the real world. A good 2 years of software experience in Python, Shell Scripting, and Databases. Expert in Crawling & scraping using any libraries such as Scrapy, Beautiful-Soup, Selenium. Ability to inspect and understand the source code of a web page. Sound knowledge of XPATH and HTML DOM. Expertise with techniques and tools for crawling, extracting, and processing data (e.g., Scrapy, pandas, SQL, Beautiful-Soup, Selenium web-driver, Requests, etc.) Expertise in extracting data from multiple disparate sources including Web, PDF, images, etc. Experience with in-browser development tools like the chrome developer tool is a plus. Expertise in bypassing Bot Detection Techniques. Expertise in using HTTP Proxy techniques to protect web scrapers against site ban, IP leak, browser crash, CAPTCHA, and proxy failure. Experience with Unit Testing. Experience with version control systems such as SVN or Git. Proficiency with Linux/Unix. Experience with designing and configuring cloud infrastructures. Experience containerizing workloads with Docker. Web Restful APIs / Microservices Development Experience. Good knowledge of distributed technologies, real-time systems of high throughput, low latency, and highly scalable.

Signals

Skill backend-engineer
0.21
Alias data-engineer
1.00
KRA data-engineer
0.59

Post-classification

Centroidupdated · n=433
Alias collision log
New-role queue
New skills captured19
New KRA captured

Captured for admin review

Shell Scripting primary Data Engineer pending
Scrapy primary Data Engineer pending
Beautiful Soup primary Data Engineer pending
Selenium primary Data Engineer pending
pandas primary Data Engineer pending
XPath primary Data Engineer pending
HTML DOM primary Data Engineer pending
Requests primary Data Engineer pending
PDF primary Data Engineer pending
SVN Data Engineer pending
Linux primary Data Engineer pending
Unix primary Data Engineer pending
Real-time Systems Data Engineer pending
High Throughput Systems Data Engineer pending
Low Latency Systems Data Engineer pending
Scalability Data Engineer pending
Chrome Developer Tools Data Engineer pending
HTTP Proxy primary Data Engineer pending
CAPTCHA Data Engineer pending
Status: completed Created: 2026-05-27T16:26:06.127898Z Updated: 2026-05-27T16:28:52.851207Z API 3 duration: 67297 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 centers on building and maintaining data crawling, scraping, ingestion, integration, and infrastructure systems, which aligns best with Data Engineer.

Matched skills

PythonShell ScriptingDatabasesScrapyBeautiful-SoupSeleniumpandasSQLRequestsXPATHHTML DOMLinux/UnixDockerGitSVN

Matched dimensions

Web Data Ingestion and CrawlingData Extraction and ProcessingData Pipeline and Infrastructure EngineeringData Quality and IntegrityTesting and MonitoringCloud and Containerized DeploymentThird-Party Data Integration

Matched KRAs

Design and implement the data crawling architectureDevelop a large-scale crawling systemBuild APIs on top of itDesign, implement and maintain data infrastructureAuthor tests to validate data availability and integrityImprove data reliability, efficiency, and qualityWork with little supervision to research and test solutions

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 - OT Solutions Tech Pvt Ltd
Position – Data Engineer


Job description 


Role: Data Engineer
Location: Indore
Type: IT Services & Consulting
Functional Area: Engineering - Software Employment
Type: Full Time, Permanent
Education: UG: B.Sc. , BCA or B.Tech/B.E. in Any Specialization
Salary: ₹ 4,00,000 - 7,50,000 L.P.A.
Experience: 1-3 Years
Working hours: 6:00 PM to 3:30 A.M


Roles and Responsibilities 


 Above anything else we are looking for a team player who can work harmonically within the team. Design and implement the data crawling architecture and a large-scale crawling system. Develop not just large-scale scraping tools but also data integrity, health, and monitoring systems. Collaborate with data and analytics experts to understand/anticipate requirements and strive for greater functionality in our data gathering system. Should be applied and set to fetch data from multiple online sources, cleanse it, and build APIs on top of it if required. Design, implement and maintain various components of our data infrastructure (Scraping data from Multiple sources and storing it in a formatted manner). Web crawlers/scrapers for a wide variety of alternative datasets. Data extractors for PDF, Images, and various other kinds of raw documents. Third-Party Data Integrations if required. Incrementally improve the quality of our offerings. Author tests to validate data availability and integrity. Recommend and sometimes implement ways to improve data reliability, efficiency, and quality of data gathering processes. Work well in the team with little supervision to research and test innovative solutions.

Desired Candidate Profile


2+ years of web crawling/ scraping experience is recommended. A solid foundation in computer science, with strong proficiencies in data structures, algorithms, and software design and how they impact the efficiency of the system in the real world. A good 2 years of software experience in Python, Shell Scripting, and Databases. Expert in Crawling & scraping using any libraries such as Scrapy, Beautiful-Soup, Selenium. Ability to inspect and understand the source code of a web page. Sound knowledge of XPATH and HTML DOM. Expertise with techniques and tools for crawling, extracting, and processing data (e.g., Scrapy, pandas, SQL, Beautiful-Soup, Selenium web-driver, Requests, etc.) Expertise in extracting data from multiple disparate sources including Web, PDF, images, etc. Experience with in-browser development tools like the chrome developer tool is a plus. Expertise in bypassing Bot Detection Techniques. Expertise in using HTTP Proxy techniques to protect web scrapers against site ban, IP leak, browser crash, CAPTCHA, and proxy failure. Experience with Unit Testing. Experience with version control systems such as SVN or Git. Proficiency with Linux/Unix. Experience with designing and configuring cloud infrastructures. Experience containerizing workloads with Docker. Web Restful APIs / Microservices Development Experience. Good knowledge of distributed technologies, real-time systems of high throughput, low latency, and highly scalable.

Perks and Benefits

* Employee Discounts.
* Paid sick days.
* Performance Bonus.


Note: Only those who are ready to relocate to Indore.

Skills from this JD

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

Python Primary 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, Fullstack Developer

  • Programming Languages & DSLs Catalog dimension db id 475

    Library dimension (catalog)

    Roles linked in library: Engineering Manager

  • Programming Languages and Scripting Catalog dimension db id 59

    Library dimension (catalog)

    Roles linked in library: Cyber Security Engineer

  • Programming Languages for Data Work Catalog dimension db id 21

    Library dimension (catalog)

    Roles linked in library: Data Engineer

  • Programming Languages for ML Systems Catalog dimension db id 39

    Library dimension (catalog)

    Roles linked in library: ML Engineer, MLOps Engineer

  • Programming Languages for XR Catalog dimension db id 97

    Library dimension (catalog)

    Roles linked in library: AR/VR Engineer

  • Python Programming Catalog dimension db id 290

    Library dimension (catalog)

    Roles linked in library: Python Backend Developer

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
Cloud Security Scripting & DSL Languages
cloud-security-scripting-dsl-languages
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Programming Languages
programming-languages
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Programming Languages & DSLs
programming-languages-dsls
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Programming Languages and Scripting
programming-languages-and-scripting
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Programming Languages for Data Work
programming-languages-for-data-work
Existing dimension (library) · Role↔dimension saved
Programming Languages for ML Systems
programming-languages-for-ml-systems
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Programming Languages for XR
programming-languages-for-xr
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Python Programming
python-programming
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Shell Scripting 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
Programming Languages
Sub-category
general
Skill nature
LANGUAGE
Volatility
STABLE
Typical lifespan
EVERGREEN
Version strategy
UNVERSIONED
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 & DSLs Catalog dimension db id 475

    Library dimension (catalog)

    Roles linked in library: Engineering Manager

  • Programming Languages for Data Work Catalog dimension db id 21

    Library dimension (catalog)

    Roles linked in library: Data Engineer

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
Pega Programming Languages & DSLs
pega-programming-languages-dsls
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Programming Languages & DSLs
programming-languages-dsls
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Programming Languages for Data Work
programming-languages-for-data-work
Existing dimension (library) · Role↔dimension saved
Scrapy 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
Web Frameworks
Sub-category
general
Skill nature
TOOL
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
Beautiful Soup 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
Web Frameworks
Sub-category
general
Skill nature
TOOL
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
Selenium 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
Testing Tools
Sub-category
general
Skill nature
TOOL
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
pandas 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
TOOL
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
XPath 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
Web Technologies
Sub-category
general
Skill nature
CONCEPT
Volatility
STABLE
Typical lifespan
EVERGREEN
Version strategy
UNVERSIONED
HTML DOM 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
Web Technologies
Sub-category
general
Skill nature
CONCEPT
Volatility
STABLE
Typical lifespan
EVERGREEN
Version strategy
UNVERSIONED
Requests 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
Web Frameworks
Sub-category
general
Skill nature
TOOL
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
PDF 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
File Formats
Sub-category
general
Skill nature
CONCEPT
Volatility
STABLE
Typical lifespan
EVERGREEN
Version strategy
UNVERSIONED
Git Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: Git id=1002 · git

Aliases — catalog

  • Git (CANONICAL)

Context tags (catalog)

CI/CD GitHub GitLab branching checkout clone commit fork merging pull request rebase remote repository stash versioning

Stored enrichment (catalog DB)

Category
Tool
Sub-category
Version Control Tool
Vendor
Linus Torvalds
License
gpl_v2
Year introduced
2005
Confidence
0.99
Version strategy
NOT_APPLICABLE

Maturity reasoning: Git is a hiring-pipeline staple: it appears in the vast majority of software engineering job descriptions and is the default VCS on GitHub/GitLab/Bitbucket.

Skill profile (library / DB)

Skill nature
TOOL
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
13
Sub-category id
730
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
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
SVN 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
Version Control Systems
Sub-category
general
Skill nature
TOOL
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
Linux 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
Operating Systems
Sub-category
general
Skill nature
PLATFORM
Volatility
STABLE
Typical lifespan
EVERGREEN
Version strategy
UNVERSIONED
Unix 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
Operating Systems
Sub-category
general
Skill nature
PLATFORM
Volatility
STABLE
Typical lifespan
EVERGREEN
Version strategy
UNVERSIONED
Docker Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: Docker id=61 · docker

Aliases — catalog

  • Docker (CANONICAL) primary

Context tags (catalog)

CI/CD Compose DevOps Docker Compose Docker Swarm Dockerfile Kubernetes build pipeline container container lifecycle container orchestration container registry container security containerization containers image image registry images immutable infrastructure lightweight virtualization microservices networking orchestration port mapping registry scalability service discovery swarm volume volume management

Stored enrichment (catalog DB)

Category
Tool
Sub-category
Containerization Tool
Vendor
Docker, Inc.
License
apache_2
Year introduced
2013
Confidence
0.98
Version strategy
NOT_APPLICABLE

Maturity reasoning: Docker is a hiring-pipeline staple: it appears in many DevOps, backend, and platform JDs, and remains a standard containerization tool alongside Kubernetes in production stacks.

Skill profile (library / DB)

Skill nature
TOOL
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
13
Sub-category id
63
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • Containerization and Image Builds Catalog dimension db id 152

    Library dimension (catalog)

    Roles linked in library: DevOps Engineer

  • Deployment and Cloud Platforms Catalog dimension db id 418

    Library dimension (catalog)

    Roles linked in library: Ruby Backend Developer

  • Deployment and Runtime Configuration Catalog dimension db id 13

    Library dimension (catalog)

    Roles linked in library: .NET Backend Developer, Backend Developer, Go Backend Developer, PHP Backend Developer

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
Containerization and Image Builds
containerization-and-image-builds
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Deployment and Cloud Platforms
deployment-and-cloud-platforms
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Deployment and Runtime Configuration
deployment-and-runtime-configuration
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
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, 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: Engineering Manager, 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)
Distributed Systems Secondary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: Distributed Systems id=1369 · distributed-systems

Aliases — catalog

  • Distributed Systems (CANONICAL)

Context tags (catalog)

CAP theorem Docker Swarm Kafka MapReduce Zookeeper consensus algorithms distributed databases eventual consistency fault tolerance gRPC load balancing message queues microservices replication sharding

Stored enrichment (catalog DB)

Category
Concept
Sub-category
Distributed Systems
Confidence
0.98
Version strategy
NOT_APPLICABLE

Maturity reasoning: Common hiring requirement in backend/platform JDs at large tech firms; appears across AWS, Kafka, microservices, and systems roles, with strong GitHub/Stack Overflow activity and no sunset signal.

Skill profile (library / DB)

Skill nature
CONCEPT
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
2
Sub-category id
1035
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • Cloud Platforms Catalog dimension db id 20

    Library dimension (catalog)

    Roles linked in library: .NET Backend Developer, Backend Developer, Cyber Security Engineer, Data Engineer, DevOps Engineer, Fullstack Developer, Go Backend Developer, Java Backend Developer, Kotlin Backend Developer, ML Engineer, MLOps Engineer, Node.js Backend Developer, Python Backend Developer, Scala Backend Developer

  • Performance and Scalability Tuning Catalog dimension db id 11

    Library dimension (catalog)

    Roles linked in library: .NET Backend Developer, Backend Developer, Node.js Backend Developer, PHP Backend Developer, Python Backend Developer

  • React Frontend Development Catalog dimension db id 96

    Library dimension (catalog)

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
Cloud Platforms
cloud-platforms
Existing dimension (library) · Role↔dimension saved
Performance and Scalability Tuning
performance-and-scalability-tuning
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)
Real-time Systems 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
Concepts
Sub-category
general
Skill nature
CONCEPT
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
High Throughput Systems 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
Concepts
Sub-category
general
Skill nature
CONCEPT
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
Low Latency Systems 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
Concepts
Sub-category
general
Skill nature
CONCEPT
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
Scalability 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
Concepts
Sub-category
general
Skill nature
CONCEPT
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
Unit Testing Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: Unit Testing id=517 · unit-testing

Aliases — catalog

  • Unit Testing (CANONICAL)

Context tags (catalog)

JUnit NUnit TDD arrange-act-assert assertions code coverage fixtures mocking pytest regression stubs test cases test doubles test runner xUnit

Stored enrichment (catalog DB)

Category
Methodology
Sub-category
Testing Methodology
Confidence
0.98
Version strategy
NOT_APPLICABLE

Maturity reasoning: Unit testing is a standard hiring requirement across software JDs and appears in mainstream frameworks/docs; GitHub and Stack Overflow usage remain consistently high, with no successor replacing it.

Skill profile (library / DB)

Skill nature
METHODOLOGY
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
8
Sub-category id
44
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
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Chrome Developer Tools Secondary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: Chrome DevTools id=701 · chrome-devtools

Aliases — catalog

  • Chrome DevTools (CANONICAL) primary

Context tags (catalog)

Application panel CSS debugging Chrome extensions Console DOM inspection Debugger Device mode Elements panel HAR JavaScript debugging Lighthouse Memory profiling Network panel Performance profiling Responsive design mode Security panel Sources panel Workspaces XHR breakpoints console coverage event listeners memory leaks network tab performance profiling responsive design mode source maps

Stored enrichment (catalog DB)

Category
Tool
Sub-category
Browser Developer Tool
Vendor
Google
License
apache_2
Year introduced
2011
Confidence
0.99
Version strategy
NOT_APPLICABLE

Maturity reasoning: Chrome DevTools is a standard browser debugging tool and appears routinely in frontend/web JDs for debugging, performance profiling, and network inspection; no vendor sunset or replacement signal exists.

Skill profile (library / DB)

Skill nature
TOOL
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
13
Sub-category id
508
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • Release Readiness and Browser Compatibility Catalog dimension db id 129

    Library dimension (catalog)

    Roles linked in library: Angular Frontend Developer, Frontend Developer, React Frontend Developer, Vue Frontend Developer, Web Developer

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
Release Readiness and Browser Compatibility
release-readiness-and-browser-compatibility
Skipped — no persistable v3 meta for new skill
skill_not_in_db_v3_proposed
HTTP Proxy 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
Networking
Sub-category
general
Skill nature
CONCEPT
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
CAPTCHA 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
Web Security
Sub-category
general
Skill nature
CONCEPT
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED

All API 3 persistence rows

Same grid as the skill-extractor “Persistence items” table: one row per (skill × dimension) work item.

Skill Tag Dimension Skill↔dim Role↔dim Outcome Notes
Python in_db
Cloud Security Scripting & DSL Languages
cloud-security-scripting-dsl-languages
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Python in_db
Programming Languages
programming-languages
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Python in_db
Programming Languages & DSLs
programming-languages-dsls
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Python in_db
Programming Languages and Scripting
programming-languages-and-scripting
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Python in_db
Programming Languages for Data Work
programming-languages-for-data-work
Existing dimension (library) · Role↔dimension saved
Python in_db
Programming Languages for ML Systems
programming-languages-for-ml-systems
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Python in_db
Programming Languages for XR
programming-languages-for-xr
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Python in_db
Python Programming
python-programming
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
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 & DSLs
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
Git in_db
React Frontend Development
d_init_01
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Docker in_db
Containerization and Image Builds
containerization-and-image-builds
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Docker in_db
Deployment and Cloud Platforms
deployment-and-cloud-platforms
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Docker in_db
Deployment and Runtime Configuration
deployment-and-runtime-configuration
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
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)
Distributed Systems in_db
Cloud Platforms
cloud-platforms
Existing dimension (library) · Role↔dimension saved
Distributed Systems in_db
Performance and Scalability Tuning
performance-and-scalability-tuning
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Distributed Systems in_db
React Frontend Development
d_init_01
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Unit Testing in_db
React Frontend Development
d_init_01
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Chrome Developer Tools new
Release Readiness and Browser Compatibility
release-readiness-and-browser-compatibility
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 Shell Scripting | type=Programming Languages subtype=general nature=LANGUAGE lifespan=EVERGREEN
canonical_skill_proposed Scrapy | type=Web Frameworks subtype=general nature=TOOL lifespan=MULTI_YEAR
canonical_skill_proposed Beautiful Soup | type=Web Frameworks subtype=general nature=TOOL lifespan=MULTI_YEAR
canonical_skill_proposed Selenium | type=Testing Tools subtype=general nature=TOOL lifespan=MULTI_YEAR
canonical_skill_proposed pandas | type=Data Engineering Tools subtype=general nature=TOOL lifespan=MULTI_YEAR
canonical_skill_proposed XPath | type=Web Technologies subtype=general nature=CONCEPT lifespan=EVERGREEN
canonical_skill_proposed HTML DOM | type=Web Technologies subtype=general nature=CONCEPT lifespan=EVERGREEN
canonical_skill_proposed Requests | type=Web Frameworks subtype=general nature=TOOL lifespan=MULTI_YEAR
canonical_skill_proposed PDF | type=File Formats subtype=general nature=CONCEPT lifespan=EVERGREEN
canonical_skill_proposed SVN | type=Version Control Systems subtype=general nature=TOOL lifespan=MULTI_YEAR
canonical_skill_proposed Linux | type=Operating Systems subtype=general nature=PLATFORM lifespan=EVERGREEN
canonical_skill_proposed Unix | type=Operating Systems subtype=general nature=PLATFORM lifespan=EVERGREEN
canonical_skill_proposed Real-time Systems | type=Concepts subtype=general nature=CONCEPT lifespan=MULTI_YEAR
canonical_skill_proposed High Throughput Systems | type=Concepts subtype=general nature=CONCEPT lifespan=MULTI_YEAR
canonical_skill_proposed Low Latency Systems | type=Concepts subtype=general nature=CONCEPT lifespan=MULTI_YEAR
canonical_skill_proposed Scalability | type=Concepts subtype=general nature=CONCEPT lifespan=MULTI_YEAR
canonical_skill_proposed HTTP Proxy | type=Networking subtype=general nature=CONCEPT lifespan=MULTI_YEAR
canonical_skill_proposed CAPTCHA | type=Web Security subtype=general nature=CONCEPT lifespan=MULTI_YEAR
dimension_skill_link_proposed Chrome Developer Tools ↔ Release Readiness and Browser Compatibility
nano JD Parser — gpt-4.1-nano click to toggle
RoleData Engineer
CompanyOT Solutions Tech Pvt Ltd
Experience1-3 Years
CTC{'max': 7.5, 'min': 4, 'raw': '₹ 4,00,000 - 7,50,000 L.P.A.', 'period': 'annual', 'currency': 'INR'}
DomainIT Services & Consulting
Location Indore, India (onsite)
JD type pass
Show raw JSON
{
  "JD_type": "pass",
  "about_company": null,
  "certifications": [],
  "company_name": "OT Solutions Tech Pvt Ltd",
  "ctc": {
    "currency": "INR",
    "max": 7.5,
    "min": 4,
    "period": "annual",
    "raw": "\u20b9 4,00,000 - 7,50,000 L.P.A."
  },
  "domain": {
    "primary": {
      "aliases": [
        "IT Consulting",
        "Technology Services"
      ],
      "domain": "IT Services \u0026 Consulting"
    },
    "secondary": null
  },
  "education": [
    {
      "level": "Bachelor\u0027s",
      "qualification": "BSC/BCA/BTECH/BE - Any Specialization",
      "raw": "UG: B.Sc. , BCA or B.Tech/B.E. in Any Specialization",
      "requirement": "required"
    }
  ],
  "experience": {
    "max": 3,
    "min": 1,
    "raw": "1-3 Years"
  },
  "job_locations": [
    {
      "aliases": [
        "Indore, MP"
      ],
      "city": "Indore",
      "country": "India",
      "state": null,
      "work_mode": "onsite"
    }
  ],
  "role": "Data Engineer",
  "role_aliases": [
    "Data Engineer",
    "Data Developer",
    "Data Analyst"
  ],
  "role_archetype": "Data",
  "roles_and_responsibilities": [
    {
      "bullet_count": 0,
      "heading": "Roles and Responsibilities",
      "heading_was_present": true,
      "source_marker": {
        "first_5_words": "Above anything else we are",
        "last_5_words": "research and test innovative solutions."
      },
      "text": "Above anything else we are looking for a team player who can work harmonically within the team. Design and implement the data crawling architecture and a large-scale crawling system. Develop not just large-scale scraping tools but also data integrity, health, and monitoring systems. Collaborate with data and analytics experts to understand/anticipate requirements and strive for greater functionality in our data gathering system. Should be applied and set to fetch data from multiple online sources, cleanse it, and build APIs on top of it if required. Design, implement and maintain various components of our data infrastructure (Scraping data from Multiple sources and storing it in a formatted manner). Web crawlers/scrapers for a wide variety of alternative datasets. Data extractors for PDF, Images, and various other kinds of raw documents. Third-Party Data Integrations if required. Incrementally improve the quality of our offerings. Author tests to validate data availability and integrity. Recommend and sometimes implement ways to improve data reliability, efficiency, and quality of data gathering processes. Work well in the team with little supervision to research and test innovative solutions.",
      "word_count": 202
    },
    {
      "bullet_count": 0,
      "heading": "Desired Candidate Profile",
      "heading_was_present": true,
      "source_marker": {
        "first_5_words": "2+ years of web crawling/",
        "last_5_words": "high throughput, low latency, and highly scalable."
      },
      "text": "2+ years of web crawling/ scraping experience is recommended. A solid foundation in computer science, with strong proficiencies in data structures, algorithms, and software design and how they impact the efficiency of the system in the real world. A good 2 years of software experience in Python, Shell Scripting, and Databases. Expert in Crawling \u0026 scraping using any libraries such as Scrapy, Beautiful-Soup, Selenium. Ability to inspect and understand the source code of a web page. Sound knowledge of XPATH and HTML DOM. Expertise with techniques and tools for crawling, extracting, and processing data (e.g., Scrapy, pandas, SQL, Beautiful-Soup, Selenium web-driver, Requests, etc.) Expertise in extracting data from multiple disparate sources including Web, PDF, images, etc. Experience with in-browser development tools like the chrome developer tool is a plus. Expertise in bypassing Bot Detection Techniques. Expertise in using HTTP Proxy techniques to protect web scrapers against site ban, IP leak, browser crash, CAPTCHA, and proxy failure. Experience with Unit Testing. Experience with version control systems such as SVN or Git. Proficiency with Linux/Unix. Experience with designing and configuring cloud infrastructures. Experience containerizing workloads with Docker. Web Restful APIs / Microservices Development Experience. Good knowledge of distributed technologies, real-time systems of high throughput, low latency, and highly scalable.",
      "word_count": 307
    }
  ],
  "urls": []
}
API 1 — extract-from-jd click to toggle
{
  "final_skills": [
    {
      "is_primary": true,
      "skill_name": "Python"
    },
    {
      "is_primary": true,
      "skill_name": "Shell Scripting"
    },
    {
      "is_primary": true,
      "skill_name": "SQL"
    },
    {
      "is_primary": true,
      "skill_name": "Scrapy"
    },
    {
      "is_primary": true,
      "skill_name": "Beautiful Soup"
    },
    {
      "is_primary": true,
      "skill_name": "Selenium"
    },
    {
      "is_primary": true,
      "skill_name": "pandas"
    },
    {
      "is_primary": true,
      "skill_name": "XPath"
    },
    {
      "is_primary": true,
      "skill_name": "HTML DOM"
    },
    {
      "is_primary": true,
      "skill_name": "Requests"
    },
    {
      "is_primary": true,
      "skill_name": "PDF"
    },
    {
      "is_primary": true,
      "skill_name": "Git"
    },
    {
      "is_primary": false,
      "skill_name": "SVN"
    },
    {
      "is_primary": true,
      "skill_name": "Linux"
    },
    {
      "is_primary": true,
      "skill_name": "Unix"
    },
    {
      "is_primary": true,
      "skill_name": "Docker"
    },
    {
      "is_primary": true,
      "skill_name": "REST"
    },
    {
      "is_primary": true,
      "skill_name": "Microservices"
    },
    {
      "is_primary": false,
      "skill_name": "Distributed Systems"
    },
    {
      "is_primary": false,
      "skill_name": "Real-time Systems"
    },
    {
      "is_primary": false,
      "skill_name": "High Throughput Systems"
    },
    {
      "is_primary": false,
      "skill_name": "Low Latency Systems"
    },
    {
      "is_primary": false,
      "skill_name": "Scalability"
    },
    {
      "is_primary": true,
      "skill_name": "Unit Testing"
    },
    {
      "is_primary": false,
      "skill_name": "Chrome Developer Tools"
    },
    {
      "is_primary": true,
      "skill_name": "HTTP Proxy"
    },
    {
      "is_primary": false,
      "skill_name": "CAPTCHA"
    }
  ],
  "jd_role": {
    "display_name": "Data Engineer",
    "rationale": null,
    "role_aliases": [
      "Data Engineer",
      "Data Developer",
      "Data Analyst"
    ],
    "role_archetype": "Data",
    "slug": ""
  },
  "nano_parsed": {
    "JD_type": "pass",
    "about_company": null,
    "certifications": [],
    "company_name": "OT Solutions Tech Pvt Ltd",
    "ctc": {
      "currency": "INR",
      "max": 7.5,
      "min": 4,
      "period": "annual",
      "raw": "\u20b9 4,00,000 - 7,50,000 L.P.A."
    },
    "domain": {
      "primary": {
        "aliases": [
          "IT Consulting",
          "Technology Services"
        ],
        "domain": "IT Services \u0026 Consulting"
      },
      "secondary": null
    },
    "education": [
      {
        "level": "Bachelor\u0027s",
        "qualification": "BSC/BCA/BTECH/BE - Any Specialization",
        "raw": "UG: B.Sc. , BCA or B.Tech/B.E. in Any Specialization",
        "requirement": "required"
      }
    ],
    "experience": {
      "max": 3,
      "min": 1,
      "raw": "1-3 Years"
    },
    "job_locations": [
      {
        "aliases": [
          "Indore, MP"
        ],
        "city": "Indore",
        "country": "India",
        "state": null,
        "work_mode": "onsite"
      }
    ],
    "role": "Data Engineer",
    "role_aliases": [
      "Data Engineer",
      "Data Developer",
      "Data Analyst"
    ],
    "role_archetype": "Data",
    "roles_and_responsibilities": [
      {
        "bullet_count": 0,
        "heading": "Roles and Responsibilities",
        "heading_was_present": true,
        "source_marker": {
          "first_5_words": "Above anything else we are",
          "last_5_words": "research and test innovative solutions."
        },
        "text": "Above anything else we are looking for a team player who can work harmonically within the team. Design and implement the data crawling architecture and a large-scale crawling system. Develop not just large-scale scraping tools but also data integrity, health, and monitoring systems. Collaborate with data and analytics experts to understand/anticipate requirements and strive for greater functionality in our data gathering system. Should be applied and set to fetch data from multiple online sources, cleanse it, and build APIs on top of it if required. Design, implement and maintain various components of our data infrastructure (Scraping data from Multiple sources and storing it in a formatted manner). Web crawlers/scrapers for a wide variety of alternative datasets. Data extractors for PDF, Images, and various other kinds of raw documents. Third-Party Data Integrations if required. Incrementally improve the quality of our offerings. Author tests to validate data availability and integrity. Recommend and sometimes implement ways to improve data reliability, efficiency, and quality of data gathering processes. Work well in the team with little supervision to research and test innovative solutions.",
        "word_count": 202
      },
      {
        "bullet_count": 0,
        "heading": "Desired Candidate Profile",
        "heading_was_present": true,
        "source_marker": {
          "first_5_words": "2+ years of web crawling/",
          "last_5_words": "high throughput, low latency, and highly scalable."
        },
        "text": "2+ years of web crawling/ scraping experience is recommended. A solid foundation in computer science, with strong proficiencies in data structures, algorithms, and software design and how they impact the efficiency of the system in the real world. A good 2 years of software experience in Python, Shell Scripting, and Databases. Expert in Crawling \u0026 scraping using any libraries such as Scrapy, Beautiful-Soup, Selenium. Ability to inspect and understand the source code of a web page. Sound knowledge of XPATH and HTML DOM. Expertise with techniques and tools for crawling, extracting, and processing data (e.g., Scrapy, pandas, SQL, Beautiful-Soup, Selenium web-driver, Requests, etc.) Expertise in extracting data from multiple disparate sources including Web, PDF, images, etc. Experience with in-browser development tools like the chrome developer tool is a plus. Expertise in bypassing Bot Detection Techniques. Expertise in using HTTP Proxy techniques to protect web scrapers against site ban, IP leak, browser crash, CAPTCHA, and proxy failure. Experience with Unit Testing. Experience with version control systems such as SVN or Git. Proficiency with Linux/Unix. Experience with designing and configuring cloud infrastructures. Experience containerizing workloads with Docker. Web Restful APIs / Microservices Development Experience. Good knowledge of distributed technologies, real-time systems of high throughput, low latency, and highly scalable.",
        "word_count": 307
      }
    ],
    "urls": []
  },
  "rejected": false,
  "rejection_reason": null,
  "run_id": "ed0f46b3-a688-41c4-b60e-a7f230eb8e50",
  "stage3_signals": {
    "alias_found": true,
    "alias_match_roles": [
      {
        "display_name": "Data Engineer",
        "kra_matches": null,
        "matched_count": null,
        "matched_skills": null,
        "role_id": 2,
        "score": 1.0,
        "slug": "data-engineer",
        "total_count": null
      },
      {
        "display_name": "Data Analyst",
        "kra_matches": null,
        "matched_count": null,
        "matched_skills": null,
        "role_id": 143,
        "score": 1.0,
        "slug": "data-analyst",
        "total_count": null
      }
    ],
    "kra_match_roles": [
      {
        "display_name": "Data Engineer",
        "kra_matches": [
          {
            "kra_text": "Works with data analysts, data scientists, and business stakeholders to define data models, ingestion schedules, and data delivery requirements.",
            "sentence": "Collaborate with data and analytics experts to understand/anticipate requirements and strive for greater functionality in our data gathering system.",
            "similarity": 0.6304
          },
          {
            "kra_text": "Implements data quality validation rules, reconciliation checks, and anomaly detection to ensure data completeness, accuracy, and consistency.",
            "sentence": "Author tests to validate data availability and integrity.",
            "similarity": 0.5798
          },
          {
            "kra_text": "Implements data quality validation rules, reconciliation checks, and anomaly detection to ensure data completeness, accuracy, and consistency.",
            "sentence": "Recommend and sometimes implement ways to improve data reliability, efficiency, and quality of data gathering processes.",
            "similarity": 0.5679
          }
        ],
        "matched_count": null,
        "matched_skills": null,
        "role_id": 2,
        "score": 0.5927,
        "slug": "data-engineer",
        "total_count": null
      },
      {
        "display_name": "Flutter Developer",
        "kra_matches": [
          {
            "kra_text": "integrate external APIs and data sources",
            "sentence": "Should be applied and set to fetch data from multiple online sources, cleanse it, and build APIs on top of it if required.",
            "similarity": 0.5754
          },
          {
            "kra_text": "collaborate with design, product, and backend teams",
            "sentence": "Collaborate with data and analytics experts to understand/anticipate requirements and strive for greater functionality in our data gathering system.",
            "similarity": 0.5381
          },
          {
            "kra_text": "integrate external APIs and data sources",
            "sentence": "Third-Party Data Integrations if required.",
            "similarity": 0.5099
          }
        ],
        "matched_count": null,
        "matched_skills": null,
        "role_id": 74,
        "score": 0.5412,
        "slug": "flutter-developer",
        "total_count": null
      },
      {
        "display_name": ".NET Backend Developer",
        "kra_matches": [
          {
            "kra_text": "internal and third-party system integration",
            "sentence": "Third-Party Data Integrations if required.",
            "similarity": 0.6213
          },
          {
            "kra_text": "validation and error handling",
            "sentence": "Author tests to validate data availability and integrity.",
            "similarity": 0.5027
          },
          {
            "kra_text": "service interface design and implementation",
            "sentence": "Web Restful APIs / Microservices Development Experience.",
            "similarity": 0.4254
          }
        ],
        "matched_count": null,
        "matched_skills": null,
        "role_id": 83,
        "score": 0.5164,
        "slug": "dotnet-backend-developer",
        "total_count": null
      },
      {
        "display_name": "Svelte Frontend Developer",
        "kra_matches": [
          {
            "kra_text": "backend data integration",
            "sentence": "Third-Party Data Integrations if required.",
            "similarity": 0.5672
          },
          {
            "kra_text": "backend data integration",
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            "similarity": 0.499
          },
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            "kra_text": "backend data integration",
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          }
        ],
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        "matched_skills": null,
        "role_id": 92,
        "score": 0.5156,
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      },
      {
        "display_name": "Backend Developer",
        "kra_matches": [
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            "similarity": 0.5145
          },
          {
            "kra_text": "Configures Docker containers, deployment descriptors, environment variables, and CI/CD pipeline stages for backend service releases.",
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            "similarity": 0.491
          },
          {
            "kra_text": "Integrates with third-party services, payment gateways, messaging queues like Kafka or RabbitMQ, and internal microservices via HTTP and event-driven patterns.",
            "sentence": "Third-Party Data Integrations if required.",
            "similarity": 0.4862
          }
        ],
        "matched_count": null,
        "matched_skills": null,
        "role_id": 1,
        "score": 0.4972,
        "slug": "backend-engineer",
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      }
    ],
    "skill_match_roles": [
      {
        "display_name": "Backend Developer",
        "kra_matches": null,
        "matched_count": 4,
        "matched_skills": [
          "Docker",
          "Python",
          "REST",
          "microservices"
        ],
        "role_id": 1,
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        "slug": "backend-engineer",
        "total_count": 19
      },
      {
        "display_name": "Engineering Manager",
        "kra_matches": null,
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          "Python",
          "REST",
          "SQL"
        ],
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        "score": 0.1579,
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        "total_count": 19
      },
      {
        "display_name": "Fullstack Developer",
        "kra_matches": null,
        "matched_count": 2,
        "matched_skills": [
          "Python",
          "REST"
        ],
        "role_id": 15,
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      },
      {
        "display_name": "Data Engineer",
        "kra_matches": null,
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        "matched_skills": [
          "Python",
          "SQL"
        ],
        "role_id": 2,
        "score": 0.1053,
        "slug": "data-engineer",
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      },
      {
        "display_name": "Pega Developer",
        "kra_matches": null,
        "matched_count": 2,
        "matched_skills": [
          "REST",
          "SQL"
        ],
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        "score": 0.1053,
        "slug": "pega-developer",
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    ]
  },
  "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,
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      "total_count": null
    },
    "confidence": 0.95,
    "is_new_role": false,
    "llm2_fired": false,
    "llm2_reasoning": null,
    "matched_dimensions": [
      "Web Data Ingestion and Crawling",
      "Data Extraction and Processing",
      "Data Pipeline and Infrastructure Engineering",
      "Data Quality and Integrity",
      "Testing and Monitoring",
      "Cloud and Containerized Deployment",
      "Third-Party Data Integration"
    ],
    "matched_kras": [
      "Design and implement the data crawling architecture",
      "Develop a large-scale crawling system",
      "Build APIs on top of it",
      "Design, implement and maintain data infrastructure",
      "Author tests to validate data availability and integrity",
      "Improve data reliability, efficiency, and quality",
      "Work with little supervision to research and test solutions"
    ],
    "matched_skills": [
      "Python",
      "Shell Scripting",
      "Databases",
      "Scrapy",
      "Beautiful-Soup",
      "Selenium",
      "pandas",
      "SQL",
      "Requests",
      "XPATH",
      "HTML DOM",
      "Linux/Unix",
      "Docker",
      "Git",
      "SVN"
    ],
    "new_role_display_name": null,
    "new_role_slug": null,
    "queued": false,
    "reasoning": "Domain=Data Engineering \u0026 Analytics; The JD centers on building and maintaining data crawling, scraping, ingestion, integration, and infrastructure systems, which aligns best with Data Engineer.",
    "sub_role": null
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  "stage5_updates": {
    "centroid_n_after": 433,
    "centroid_updated": true,
    "collision_log_id": null,
    "new_kra_attached": null,
    "new_skills_attached": [
      {
        "is_primary": true,
        "queue_id": 20023,
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        "skill_name": "Shell Scripting",
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      },
      {
        "is_primary": true,
        "queue_id": 20024,
        "role_display_name": "Data Engineer",
        "role_slug": "data-engineer",
        "skill_name": "Scrapy",
        "status": "pending"
      },
      {
        "is_primary": true,
        "queue_id": 20026,
        "role_display_name": "Data Engineer",
        "role_slug": "data-engineer",
        "skill_name": "Beautiful Soup",
        "status": "pending"
      },
      {
        "is_primary": true,
        "queue_id": 20027,
        "role_display_name": "Data Engineer",
        "role_slug": "data-engineer",
        "skill_name": "Selenium",
        "status": "pending"
      },
      {
        "is_primary": true,
        "queue_id": 20028,
        "role_display_name": "Data Engineer",
        "role_slug": "data-engineer",
        "skill_name": "pandas",
        "status": "pending"
      },
      {
        "is_primary": true,
        "queue_id": 20029,
        "role_display_name": "Data Engineer",
        "role_slug": "data-engineer",
        "skill_name": "XPath",
        "status": "pending"
      },
      {
        "is_primary": true,
        "queue_id": 20030,
        "role_display_name": "Data Engineer",
        "role_slug": "data-engineer",
        "skill_name": "HTML DOM",
        "status": "pending"
      },
      {
        "is_primary": true,
        "queue_id": 20031,
        "role_display_name": "Data Engineer",
        "role_slug": "data-engineer",
        "skill_name": "Requests",
        "status": "pending"
      },
      {
        "is_primary": true,
        "queue_id": 20032,
        "role_display_name": "Data Engineer",
        "role_slug": "data-engineer",
        "skill_name": "PDF",
        "status": "pending"
      },
      {
        "is_primary": false,
        "queue_id": 20033,
        "role_display_name": "Data Engineer",
        "role_slug": "data-engineer",
        "skill_name": "SVN",
        "status": "pending"
      },
      {
        "is_primary": true,
        "queue_id": 20034,
        "role_display_name": "Data Engineer",
        "role_slug": "data-engineer",
        "skill_name": "Linux",
        "status": "pending"
      },
      {
        "is_primary": true,
        "queue_id": 20035,
        "role_display_name": "Data Engineer",
        "role_slug": "data-engineer",
        "skill_name": "Unix",
        "status": "pending"
      },
      {
        "is_primary": false,
        "queue_id": 20036,
        "role_display_name": "Data Engineer",
        "role_slug": "data-engineer",
        "skill_name": "Real-time Systems",
        "status": "pending"
      },
      {
        "is_primary": false,
        "queue_id": 20037,
        "role_display_name": "Data Engineer",
        "role_slug": "data-engineer",
        "skill_name": "High Throughput Systems",
        "status": "pending"
      },
      {
        "is_primary": false,
        "queue_id": 20038,
        "role_display_name": "Data Engineer",
        "role_slug": "data-engineer",
        "skill_name": "Low Latency Systems",
        "status": "pending"
      },
      {
        "is_primary": false,
        "queue_id": 20039,
        "role_display_name": "Data Engineer",
        "role_slug": "data-engineer",
        "skill_name": "Scalability",
        "status": "pending"
      },
      {
        "is_primary": false,
        "queue_id": 20040,
        "role_display_name": "Data Engineer",
        "role_slug": "data-engineer",
        "skill_name": "Chrome Developer Tools",
        "status": "pending"
      },
      {
        "is_primary": true,
        "queue_id": 20041,
        "role_display_name": "Data Engineer",
        "role_slug": "data-engineer",
        "skill_name": "HTTP Proxy",
        "status": "pending"
      },
      {
        "is_primary": false,
        "queue_id": 20042,
        "role_display_name": "Data Engineer",
        "role_slug": "data-engineer",
        "skill_name": "CAPTCHA",
        "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_persisted": false,
      "existing_alias_id": 67,
      "existing_alias_text": "Python",
      "input_term": "Python",
      "matched_canonical": {
        "category_id": 6,
        "display_name": "Python",
        "id": 5,
        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "LANGUAGE",
        "slug": "python",
        "sub_category_id": 96,
        "typical_lifespan": "EVERGREEN",
        "volatility": "STABLE"
      },
      "matched_via": "alias"
    },
    {
      "alias_persist_skipped_reason": "alias_text already exists for this canonical skill",
      "alias_persisted": false,
      "existing_alias_id": 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": 1613,
      "existing_alias_text": "Git",
      "input_term": "Git",
      "matched_canonical": {
        "category_id": 13,
        "display_name": "Git",
        "id": 1002,
        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "TOOL",
        "slug": "git",
        "sub_category_id": 730,
        "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": 198,
      "existing_alias_text": "Docker",
      "input_term": "Docker",
      "matched_canonical": {
        "category_id": 13,
        "display_name": "Docker",
        "id": 61,
        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "TOOL",
        "slug": "docker",
        "sub_category_id": 63,
        "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": 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": 2028,
      "existing_alias_text": "Distributed Systems",
      "input_term": "Distributed Systems",
      "matched_canonical": {
        "category_id": 2,
        "display_name": "Distributed Systems",
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        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "CONCEPT",
        "slug": "distributed-systems",
        "sub_category_id": 1035,
        "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": 865,
      "existing_alias_text": "Unit Testing",
      "input_term": "Unit Testing",
      "matched_canonical": {
        "category_id": 8,
        "display_name": "Unit Testing",
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        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "METHODOLOGY",
        "slug": "unit-testing",
        "sub_category_id": 44,
        "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": 1206,
      "existing_alias_text": "Chrome DevTools",
      "input_term": "Chrome Developer Tools",
      "matched_canonical": {
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        "display_name": "Chrome DevTools",
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        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "TOOL",
        "slug": "chrome-devtools",
        "sub_category_id": 508,
        "typical_lifespan": "EVERGREEN",
        "volatility": "STABLE"
      },
      "matched_via": "embedding_alias"
    }
  ],
  "candidate_roles": [
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      "rationale": null,
      "role_archetype": null,
      "slug": "cloud-security-engineer",
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    },
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    },
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    },
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      "display_name": "Cyber Security Engineer",
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      "slug": "cybersecurity-engineer",
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      "slug": "data-engineer",
      "source": "db"
    },
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      "display_name": "ML Engineer",
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      "slug": "ml-engineer",
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    },
    {
      "display_name": "MLOps Engineer",
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      "slug": "ml-ops-engineer",
      "source": "db"
    },
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      "display_name": "AR/VR Engineer",
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      "slug": "ar-vr-engineer",
      "source": "db"
    },
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      "role_archetype": "Engineering",
      "slug": "python-backend-developer",
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    },
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      "display_name": "Pega Developer",
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      "rationale": null,
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      "slug": "pega-developer",
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    },
    {
      "display_name": "DevOps Engineer",
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      "rationale": null,
      "role_archetype": null,
      "slug": "devops-engineer",
      "source": "db"
    },
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      "display_name": "Ruby Backend Developer",
      "id": 85,
      "rationale": null,
      "role_archetype": "Engineering",
      "slug": "ruby-backend-developer",
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    },
    {
      "display_name": ".NET Backend Developer",
      "id": 83,
      "rationale": null,
      "role_archetype": "Engineering",
      "slug": "dotnet-backend-developer",
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    },
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      "display_name": "Go Backend Developer",
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      "rationale": null,
      "role_archetype": "Engineering",
      "slug": "go-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",
      "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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      "display_name": "Node.js Backend Developer",
      "id": 82,
      "rationale": null,
      "role_archetype": "Engineering",
      "slug": "node-backend-developer",
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      "display_name": "Scala Backend Developer",
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      "rationale": null,
      "role_archetype": "Engineering",
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      "display_name": "Sitecore Dev",
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      "role_archetype": "Engineering",
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      "role_archetype": "Engineering",
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    },
    {
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      "slug": "frontend-engineer",
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      "role_archetype": "Engineering",
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      "rationale": null,
      "role_archetype": "Engineering",
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      "display_name": "Web Developer",
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  "chosen_role": {
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    "rationale": "Domain=Data Engineering \u0026 Analytics; The JD centers on building and maintaining data crawling, scraping, ingestion, integration, and infrastructure systems, which aligns best with Data Engineer.",
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    "slug": "data-engineer",
    "source": "db"
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      "dimension": {
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      ]
    },
    {
      "dimension": {
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        "source": "db"
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      "input_skill": "Python",
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        "merge_log": [],
        "placed": null,
        "relationships": null,
        "skill_id": "high-throughput-systems",
        "split_log": [],
        "typed": null,
        "warnings": []
      },
      "source_tag": "llm",
      "was_in_llm_skills": true
    },
    {
      "aliases_in_db": [],
      "canonical": null,
      "dimensions": [],
      "input_skill": "Low Latency Systems",
      "matched_via": null,
      "new_alias_persisted": false,
      "new_alias_text": null,
      "new_skill_meta": {
        "derived": {
          "category": "Concepts",
          "skill_nature": "CONCEPT",
          "sub_category": "general",
          "typical_lifespan": "MULTI_YEAR",
          "version_strategy": "UNVERSIONED",
          "volatility": "MEDIUM"
        },
        "enrichment": null,
        "keep_log": [],
        "locked_dimensions": [],
        "merge_log": [],
        "placed": null,
        "relationships": null,
        "skill_id": "low-latency-systems",
        "split_log": [],
        "typed": null,
        "warnings": []
      },
      "source_tag": "llm",
      "was_in_llm_skills": true
    },
    {
      "aliases_in_db": [],
      "canonical": null,
      "dimensions": [],
      "input_skill": "Scalability",
      "matched_via": null,
      "new_alias_persisted": false,
      "new_alias_text": null,
      "new_skill_meta": {
        "derived": {
          "category": "Concepts",
          "skill_nature": "CONCEPT",
          "sub_category": "general",
          "typical_lifespan": "MULTI_YEAR",
          "version_strategy": "UNVERSIONED",
          "volatility": "MEDIUM"
        },
        "enrichment": null,
        "keep_log": [],
        "locked_dimensions": [],
        "merge_log": [],
        "placed": null,
        "relationships": null,
        "skill_id": "scalability",
        "split_log": [],
        "typed": null,
        "warnings": []
      },
      "source_tag": "llm",
      "was_in_llm_skills": true
    },
    {
      "aliases_in_db": [
        {
          "alias_text": "Unit Testing",
          "alias_type": "CANONICAL",
          "id": 865,
          "is_primary": false,
          "match_strategy": "CASE_INSENSITIVE"
        }
      ],
      "canonical": {
        "category_id": 8,
        "display_name": "Unit Testing",
        "id": 517,
        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "METHODOLOGY",
        "slug": "unit-testing",
        "sub_category_id": 44,
        "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": "Unit Testing",
          "llm_role": null,
          "roles_from_db": []
        }
      ],
      "input_skill": "Unit Testing",
      "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": "Chrome DevTools",
          "alias_type": "CANONICAL",
          "id": 1206,
          "is_primary": true,
          "match_strategy": "CASE_INSENSITIVE"
        }
      ],
      "canonical": {
        "category_id": 13,
        "display_name": "Chrome DevTools",
        "id": 701,
        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "TOOL",
        "slug": "chrome-devtools",
        "sub_category_id": 508,
        "typical_lifespan": "EVERGREEN",
        "volatility": "STABLE"
      },
      "dimensions": [
        {
          "dimension": {
            "difficulty_hint": "well_known",
            "display_name": "Release Readiness and Browser Compatibility",
            "id": 129,
            "rationale": "Practices for verifying frontend changes across browsers, environments, and release stages. This cluster is coherent because frontend engineers often own the last-mile quality checks before shipping UI changes.",
            "slug": "release-readiness-and-browser-compatibility",
            "source": "db"
          },
          "input_skill": "Chrome Developer Tools",
          "llm_role": null,
          "roles_from_db": [
            {
              "display_name": "Angular Frontend Developer",
              "id": 90,
              "rationale": null,
              "role_archetype": "Engineering",
              "slug": "angular-frontend-developer",
              "source": "db"
            },
            {
              "display_name": "Frontend Developer",
              "id": 7,
              "rationale": null,
              "role_archetype": null,
              "slug": "frontend-engineer",
              "source": "db"
            },
            {
              "display_name": "React Frontend Developer",
              "id": 89,
              "rationale": null,
              "role_archetype": "Engineering",
              "slug": "react-frontend-developer",
              "source": "db"
            },
            {
              "display_name": "Vue Frontend Developer",
              "id": 91,
              "rationale": null,
              "role_archetype": "Engineering",
              "slug": "vue-frontend-developer",
              "source": "db"
            },
            {
              "display_name": "Web Developer",
              "id": 25,
              "rationale": null,
              "role_archetype": null,
              "slug": "web-developer",
              "source": "db"
            }
          ]
        }
      ],
      "input_skill": "Chrome Developer Tools",
      "matched_via": "embedding_alias",
      "new_alias_persisted": false,
      "new_alias_text": null,
      "new_skill_meta": null,
      "source_tag": "db",
      "was_in_llm_skills": true
    },
    {
      "aliases_in_db": [],
      "canonical": null,
      "dimensions": [],
      "input_skill": "HTTP Proxy",
      "matched_via": null,
      "new_alias_persisted": false,
      "new_alias_text": null,
      "new_skill_meta": {
        "derived": {
          "category": "Networking",
          "skill_nature": "CONCEPT",
          "sub_category": "general",
          "typical_lifespan": "MULTI_YEAR",
          "version_strategy": "UNVERSIONED",
          "volatility": "MEDIUM"
        },
        "enrichment": null,
        "keep_log": [],
        "locked_dimensions": [],
        "merge_log": [],
        "placed": null,
        "relationships": null,
        "skill_id": "http-proxy",
        "split_log": [],
        "typed": null,
        "warnings": []
      },
      "source_tag": "llm",
      "was_in_llm_skills": true
    },
    {
      "aliases_in_db": [],
      "canonical": null,
      "dimensions": [],
      "input_skill": "CAPTCHA",
      "matched_via": null,
      "new_alias_persisted": false,
      "new_alias_text": null,
      "new_skill_meta": {
        "derived": {
          "category": "Web Security",
          "skill_nature": "CONCEPT",
          "sub_category": "general",
          "typical_lifespan": "MULTI_YEAR",
          "version_strategy": "UNVERSIONED",
          "volatility": "MEDIUM"
        },
        "enrichment": null,
        "keep_log": [],
        "locked_dimensions": [],
        "merge_log": [],
        "placed": null,
        "relationships": null,
        "skill_id": "captcha",
        "split_log": [],
        "typed": null,
        "warnings": []
      },
      "source_tag": "llm",
      "was_in_llm_skills": true
    }
  ],
  "unmatched_skills": [
    "Shell Scripting",
    "Scrapy",
    "Beautiful Soup",
    "Selenium",
    "pandas",
    "XPath",
    "HTML DOM",
    "Requests",
    "PDF",
    "SVN",
    "Linux",
    "Unix",
    "Real-time Systems",
    "High Throughput Systems",
    "Low Latency Systems",
    "Scalability",
    "HTTP Proxy",
    "CAPTCHA"
  ]
}
API 3 — final-role-output
{
  "chosen_role": {
    "display_name": "Data Engineer",
    "id": 2,
    "rationale": "Domain=Data Engineering \u0026 Analytics; The JD centers on building and maintaining data crawling, scraping, ingestion, integration, and infrastructure systems, which aligns best with Data Engineer.",
    "role_archetype": null,
    "slug": "data-engineer",
    "source": "db"
  },
  "chosen_role_resolution": "in_db",
  "final_input_skills": [
    {
      "skill": "Python",
      "tag": "in_db"
    },
    {
      "skill": "Shell Scripting",
      "tag": "new"
    },
    {
      "skill": "SQL",
      "tag": "in_db"
    },
    {
      "skill": "Scrapy",
      "tag": "new"
    },
    {
      "skill": "Beautiful Soup",
      "tag": "new"
    },
    {
      "skill": "Selenium",
      "tag": "new"
    },
    {
      "skill": "pandas",
      "tag": "new"
    },
    {
      "skill": "XPath",
      "tag": "new"
    },
    {
      "skill": "HTML DOM",
      "tag": "new"
    },
    {
      "skill": "Requests",
      "tag": "new"
    },
    {
      "skill": "PDF",
      "tag": "new"
    },
    {
      "skill": "Git",
      "tag": "in_db"
    },
    {
      "skill": "SVN",
      "tag": "new"
    },
    {
      "skill": "Linux",
      "tag": "new"
    },
    {
      "skill": "Unix",
      "tag": "new"
    },
    {
      "skill": "Docker",
      "tag": "in_db"
    },
    {
      "skill": "REST",
      "tag": "in_db"
    },
    {
      "skill": "Microservices",
      "tag": "in_db"
    },
    {
      "skill": "Distributed Systems",
      "tag": "in_db"
    },
    {
      "skill": "Real-time Systems",
      "tag": "new"
    },
    {
      "skill": "High Throughput Systems",
      "tag": "new"
    },
    {
      "skill": "Low Latency Systems",
      "tag": "new"
    },
    {
      "skill": "Scalability",
      "tag": "new"
    },
    {
      "skill": "Unit Testing",
      "tag": "in_db"
    },
    {
      "skill": "Chrome Developer Tools",
      "tag": "in_db"
    },
    {
      "skill": "HTTP Proxy",
      "tag": "new"
    },
    {
      "skill": "CAPTCHA",
      "tag": "new"
    }
  ],
  "llm_cost_api1_usd": null,
  "llm_cost_api2_usd": null,
  "llm_cost_api3_usd": null,
  "llm_cost_total_usd": null,
  "persistence": {
    "items": [
      {
        "chosen_role_id": 2,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Cloud Security Scripting \u0026 DSL Languages",
          "id": 248,
          "rationale": "Proficiency in programming and domain-specific languages used to automate and script cloud security controls.",
          "slug": "cloud-security-scripting-dsl-languages",
          "source": "db"
        },
        "dimension_id": 248,
        "input_skill": "Python",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": "Cloud Security Engineer",
            "id": 23,
            "rationale": null,
            "role_archetype": null,
            "slug": "cloud-security-engineer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 5,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 2,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Programming Languages",
          "id": 1,
          "rationale": "Primary implementation languages used to build client and server feature code. Full stack engineers need enough fluency to move across layers and implement product behavior end to end.",
          "slug": "programming-languages",
          "source": "db"
        },
        "dimension_id": 1,
        "input_skill": "Python",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": "Backend Developer",
            "id": 1,
            "rationale": null,
            "role_archetype": "A Backend Engineer designs, builds, and maintains the server-side logic and data handling that power applications and services. They focus on implementing reliable business functionality, integrating with other systems, and ensuring the backend is scalable, maintainable, and observable.",
            "slug": "backend-engineer",
            "source": "db"
          },
          {
            "display_name": "Fullstack Developer",
            "id": 15,
            "rationale": null,
            "role_archetype": null,
            "slug": "full-stack-engineer",
            "source": "db"
          },
          {
            "display_name": "Fullstack Developer",
            "id": 435,
            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "fullstack-developer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 5,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 2,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Programming Languages \u0026 DSLs",
          "id": 475,
          "rationale": "Oversee and guide the selection and effective use of programming and domain\u2010specific languages in software projects.",
          "slug": "programming-languages-dsls",
          "source": "db"
        },
        "dimension_id": 475,
        "input_skill": "Python",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": "Engineering Manager",
            "id": 121,
            "rationale": null,
            "role_archetype": null,
            "slug": "engineering-manager",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 5,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 2,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Programming Languages and Scripting",
          "id": 59,
          "rationale": "Languages used to write security automation, analysis scripts, detection logic, and remediation helpers. This is the primary implementation surface for a cybersecurity engineer across tooling and response workflows.",
          "slug": "programming-languages-and-scripting",
          "source": "db"
        },
        "dimension_id": 59,
        "input_skill": "Python",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": "Cyber Security Engineer",
            "id": 5,
            "rationale": null,
            "role_archetype": null,
            "slug": "cybersecurity-engineer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 5,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 2,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Programming Languages for Data Work",
          "id": 21,
          "rationale": "Languages used to implement data pipelines, transformations, and operational glue. This is the primary coding surface for building ingestion, enrichment, and automation logic in data engineering.",
          "slug": "programming-languages-for-data-work",
          "source": "db"
        },
        "dimension_id": 21,
        "input_skill": "Python",
        "llm_role": null,
        "matched_chosen_role": true,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension saved",
        "role_dimension_saved": true,
        "roles_from_db": [
          {
            "display_name": "Data Engineer",
            "id": 2,
            "rationale": null,
            "role_archetype": null,
            "slug": "data-engineer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 5,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 2,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Programming Languages for ML Systems",
          "id": 39,
          "rationale": "Languages used to build training code, inference services, evaluation jobs, and ML glue code. This is the primary implementation surface for ML engineers across experimentation and productionization.",
          "slug": "programming-languages-for-ml-systems",
          "source": "db"
        },
        "dimension_id": 39,
        "input_skill": "Python",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": "ML Engineer",
            "id": 3,
            "rationale": null,
            "role_archetype": null,
            "slug": "ml-engineer",
            "source": "db"
          },
          {
            "display_name": "MLOps Engineer",
            "id": 16,
            "rationale": null,
            "role_archetype": null,
            "slug": "ml-ops-engineer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 5,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 2,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Programming Languages for XR",
          "id": 97,
          "rationale": "Primary implementation languages used to build immersive client features, interaction logic, and device-specific runtime behavior. This is the core coding surface for AR/VR experiences.",
          "slug": "programming-languages-for-xr",
          "source": "db"
        },
        "dimension_id": 97,
        "input_skill": "Python",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": "AR/VR Engineer",
            "id": 8,
            "rationale": null,
            "role_archetype": null,
            "slug": "ar-vr-engineer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 5,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 2,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Python Programming",
          "id": 290,
          "rationale": "Core Python language skills used to implement backend business logic, request handlers, integrations, and service internals. This is the primary coding surface for the role.",
          "slug": "python-programming",
          "source": "db"
        },
        "dimension_id": 290,
        "input_skill": "Python",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": "Python Backend Developer",
            "id": 80,
            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "python-backend-developer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 5,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 2,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Pega Programming Languages \u0026 DSLs",
          "id": 267,
          "rationale": "Programming languages and domain-specific languages used in Pega development.",
          "slug": "pega-programming-languages-dsls",
          "source": "db"
        },
        "dimension_id": 267,
        "input_skill": "SQL",
        "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": 101,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 2,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Programming Languages \u0026 DSLs",
          "id": 475,
          "rationale": "Oversee and guide the selection and effective use of programming and domain\u2010specific languages in software projects.",
          "slug": "programming-languages-dsls",
          "source": "db"
        },
        "dimension_id": 475,
        "input_skill": "SQL",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": "Engineering Manager",
            "id": 121,
            "rationale": null,
            "role_archetype": null,
            "slug": "engineering-manager",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 101,
        "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": "SQL",
        "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": 101,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
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