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Pipeline run

d8bed4ec-2eeb-4231-90e3-06c79590b876

Pipeline LLM cost (USD)
API 1: $0.0036 API 2: $0.0003 API 3: $0.0000 Total: $0.0040

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 GCP-based ETL/data pipelines, write and tune SQL for data extraction/transformation, and monitor/troubleshoot workflow issues while ensuring data quality and performance across systems.
"Design, develop, test, and maintain scalable data pipelines and software systems."
Tech stack maturity
Modern Cloud Native
BigQuery and GCP are cloud-native data platform technologies, and SQL is a mainstream modern skill set commonly used in cloud-based analytics engineering.
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 (12)
GCP BigQuery Dataproc Data Fusion Cloud SQL SQL Teradata Unix ETL Python Ab Initio ODI
Skill cluster (4 dimension groups, role-scoped)
Programming Languages for Data Work
SQL Python
Cloud Data Warehouses
BigQuery
Cloud Platforms
GCP
Cross-cutting / unaligned
Dataproc Data Fusion Cloud SQL Teradata Unix ETL Ab Initio ODI
Show KRA description ↓
• Design, develop, test, and maintain scalable data pipelines and software systems. • Collaborate with cross-functional teams to gather and understand data requirements. • Implement ETL processes using tools such as Ab Initio or ODI. • Work with GCP services including BigQuery, Dataproc, Data Fusion, and Cloud SQL. • Write and optimise SQL queries for data extraction and transformation. • Ensure data quality, integrity, and performance across systems. • Monitor and troubleshoot data workflows and system issues. • 2-4 years of experience in data engineering or related roles. • Proficient in GCP services: BigQuery, Dataproc, Data Fusion, and Cloud SQL. • Hands-on experience with ETL tools such as Ab Initio or ODI. • Strong knowledge of Unix and SQL/Teradata. • Exposure to Python is a plus. • Strong problem-solving skills and attention to detail. • Effective communicator and team collaborator. • Adaptable and proactive in dynamic environments.

Signals

Skill data-engineer
0.33
Alias data-engineer
1.00
KRA data-engineer
0.63

Post-classification

Centroidupdated · n=268
Alias collision log
New-role queue
New skills captured8
New KRA captured

Captured for admin review

Dataproc primary Data Engineer pending
Data Fusion primary Data Engineer pending
Cloud SQL primary Data Engineer pending
Teradata primary Data Engineer pending
Unix primary Data Engineer pending
ETL primary Data Engineer pending
Ab Initio Data Engineer pending
ODI Data Engineer pending
Status: completed Created: 2026-05-27T15:14:56.658888Z Updated: 2026-06-12T16:43:13.246459Z API 3 duration: 36077 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

CASE A

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

Exact alias hit on data-engineer (1.0) — no other alias at this confidence; skill_top data-engineer 0.33 does not contradict

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
0
Skipped

Job description

Who We Are

VOIS (Vodafone Intelligent Solutions) is a strategic arm of Vodafone Group Plc, creating value for customers by delivering intelligent solutions through Talent, Technology & Transformation.

As the largest shared services organisation in the global telco industry with 30,000 FTE, our portfolio of next-generation solutions and services are designed in partnership with customers across Vodafone Group, local markets, and partner markets to simplify and drive growth. With our strategic partner Accenture, we work alongside our Vodafone customers, other Telco and tech companies to drive transformation, meet the challenges of our industry and ensure we stay relevant and resilient. This partnership is a unique, industry-first model which brings together the best of in-house and 3rd party capability.

We work with customers across 28 countries from 10 VOIS locations: Albania, Egypt, Hungary, India, Romania, Spain, Turkey, UK, Germany, Ireland, and with a network of teams in Czech Republic, Italy, Greece, and Portugal.

#VOIS #BeUnrivalled #CreateTheFuture

About This Role

We are seeking a Data Engineer with 2 to 4 years of experience to design, develop, and maintain scalable data pipelines and software systems. The individual will work extensively with Google Cloud Platform (GCP) services such as BigQuery, Dataproc, Data Fusion, and Cloud SQL, while implementing ETL processes using tools like Ab Initio or Oracle Data Integrator (ODI). This role requires strong SQL skills, collaboration with cross-functional teams, and a focus on data quality and performance.

What You’ll Do

• Design, develop, test, and maintain scalable data pipelines and software systems.
• Collaborate with cross-functional teams to gather and understand data requirements.
• Implement ETL processes using tools such as Ab Initio or ODI.
• Work with GCP services including BigQuery, Dataproc, Data Fusion, and Cloud SQL.
• Write and optimise SQL queries for data extraction and transformation.
• Ensure data quality, integrity, and performance across systems.
• Monitor and troubleshoot data workflows and system issues.


Who You Are

• 2-4 years of experience in data engineering or related roles.
• Proficient in GCP services: BigQuery, Dataproc, Data Fusion, and Cloud SQL.
• Hands-on experience with ETL tools such as Ab Initio or ODI.
• Strong knowledge of Unix and SQL/Teradata.
• Exposure to Python is a plus.
• Strong problem-solving skills and attention to detail.
• Effective communicator and team collaborator.
• Adaptable and proactive in dynamic environments.


Not a perfect fit?

Concerned you may not meet every requirement? Vodafone is committed to creating an inclusive workplace where everyone can thrive. If you are excited about this role but your experience does not align exactly with every aspect of the job description, you are encouraged to apply. You may be the right candidate for this or another opportunity, and the recruitment team will support you in exploring where your skills fit best.

What's In It For You

• Opportunity to work on cutting-edge cloud technologies and data engineering projects.
• Exposure to large-scale data systems and global operations.
• Collaborative work environment with cross-functional teams.
• Career growth within a global organisation committed to innovation and transformation.


What Skills You Will Learn

• Advanced GCP services and data pipeline optimisation.
• ETL process automation and integration using industry-leading tools.
• Performance tuning for large-scale data systems.
• Best practices in data governance and quality assurance.


VOIS Equal Opportunity Employer Commitment

Vodafone recognises and celebrates the value of diversity in building a workforce that reflects the customers and communities it serves. No form of discrimination is tolerated. This includes, but is not limited to, discrimination based on race, colour, age, veteran status, gender identity, gender expression, sexual orientation, pregnancy, maternity or parental status, ethnicity, disability, religion or belief, political affiliation, trade union membership, nationality, citizenship, indigenous status, medical condition, HIV status, neurodiversity, social origin, cultural background, marital or civil partnership status, or socio-economic background.

Join Us

At Vodafone, we’re working hard to build a better future. A more connected, inclusive and sustainable world. As a dynamic global community, it's our human spirit, together with technology, that empowers us to achieve this.

We challenge and innovate in order to connect people, businesses, and communities across the world. Delighting our customers and earning their loyalty drive us, and we experiment, learn fast and get it done, together.

With us, you can be truly be yourself and belong, share inspiration, embrace new opportunities, thrive, and make a real difference.

Alert

Apply for Vodafone jobs only through the official Vodafone Careers website to avoid job scams and fraud.

#JDEnhancedByTARA

Follow us on social media and #StayConnected

• LinkedIn: https://www.linkedin.com/company/vois/
• Facebook: https://www.facebook.com/voisglobal
• Instagram: https://www.instagram.com/voisglobal/
• Chat with our employees: https://lnkd.in/dpkrcvR2

Skills from this JD

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

GCP Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: GCP id=186 · gcp

Aliases — catalog

  • GCP (CANONICAL) primary

Context tags (catalog)

Anthos App Engine Artifact Registry BigQuery Cloud Build Cloud Composer Cloud Functions Cloud Logging Cloud Monitoring Cloud Run Cloud SQL Cloud Spanner Cloud Storage Compute Engine Dataflow GKE IAM Kubernetes Pub/Sub Service Accounts Stackdriver Terraform VPC

Stored enrichment (catalog DB)

Category
Platform
Sub-category
Cloud Platform
Vendor
Google
License
other_open
Year introduced
2011
Confidence
0.99
Version strategy
NOT_APPLICABLE

Maturity reasoning: GCP appears frequently in cloud/platform job descriptions and is a major hyperscaler alongside AWS/Azure, with broad enterprise adoption and active vendor investment.

Skill profile (library / DB)

Skill nature
PLATFORM
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
9
Sub-category id
46
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • Cloud 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

  • Cloud Platforms for AI Deployment Catalog dimension db id 211

    Library dimension (catalog)

    Roles linked in library: AI Engineer

  • Cloud Provider Platforms Catalog dimension db id 131

    Library dimension (catalog)

    Roles linked in library: Cloud Architect, Cloud Security Engineer

  • Cloud Security Posture Tools Catalog dimension db id 64

    Library dimension (catalog)

    Roles linked in library: Cloud Security Engineer, Cyber Security Engineer

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
Cloud Platforms
cloud-platforms
Existing dimension (library) · Role↔dimension saved
Cloud Platforms for AI Deployment
cloud-platforms-for-ai-deployment
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Cloud Provider Platforms
cloud-provider-platforms
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Cloud Security Posture Tools
cloud-security-posture-tools
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
BigQuery Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: BigQuery id=106 · bigquery

Aliases — catalog

  • BigQuery (CANONICAL) primary

Context tags (catalog)

Cloud Storage Dataflow ELT ETL GCP Google Cloud Platform Looker Pub/Sub SQL Standard SQL clustered tables data warehouse dbt partitioned tables service account

Stored enrichment (catalog DB)

Category
Service
Sub-category
Data Warehouse Service
Vendor
Google
License
proprietary
Year introduced
2011
Confidence
0.98
Version strategy
NOT_APPLICABLE

Maturity reasoning: BigQuery appears frequently in data/analytics job descriptions and is a core Google Cloud warehouse offering, with broad enterprise adoption and strong ecosystem support.

Skill profile (library / DB)

Skill nature
CLOUD_SERVICE
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
11
Sub-category id
118
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • Cloud Data Warehouses Catalog dimension db id 22

    Library dimension (catalog)

    Roles linked in library: Data Engineer

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
Cloud Data Warehouses
cloud-data-warehouses
Existing dimension (library) · Role↔dimension saved
Dataproc 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
Cloud Platforms
Sub-category
general
Skill nature
PLATFORM
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
Data Fusion 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
Cloud SQL 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
Cloud Platforms
Sub-category
general
Skill nature
PLATFORM
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
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
Teradata 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
Databases
Sub-category
general
Skill nature
TOOL
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
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
CONCEPT
Volatility
STABLE
Typical lifespan
EVERGREEN
Version strategy
UNVERSIONED
Python Secondary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: Python id=5 · python

Aliases — catalog

  • Python (CANONICAL) primary
  • Python 2 (VERSION)
  • Python 2.x (VERSION)
  • Python 3 (VERSION)
  • Python 3.10 (VERSION)
  • Python 3.11 (VERSION)
  • Python 3.12 (VERSION)
  • Python 3.x (VERSION)
  • py (VERSION)
  • py2 (VERSION)
  • py3 (VERSION)
  • python 3 (VERSION)
  • python 3.x (VERSION)
  • python2 (VERSION)
  • python3 (VERSION)
  • python3.x (VERSION)

Context tags (catalog)

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

Stored enrichment (catalog DB)

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

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

Skill profile (library / DB)

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

Dimensions (API 2 worklist)

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

    Library dimension (catalog)

    Roles linked in library: Cloud Security Engineer

  • Programming Languages Catalog dimension db id 1

    Library dimension (catalog)

    Roles linked in library: Backend Developer, Fullstack Developer, 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)
ETL 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
PRACTICE
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
Ab Initio 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
Data Engineering Tools
Sub-category
general
Skill nature
TOOL
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
ODI 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
Data Engineering Tools
Sub-category
general
Skill nature
TOOL
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
GCP in_db
Cloud Platforms
cloud-platforms
Existing dimension (library) · Role↔dimension saved
GCP in_db
Cloud Platforms for AI Deployment
cloud-platforms-for-ai-deployment
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
GCP in_db
Cloud Provider Platforms
cloud-provider-platforms
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
GCP in_db
Cloud Security Posture Tools
cloud-security-posture-tools
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
BigQuery in_db
Cloud Data Warehouses
cloud-data-warehouses
Existing dimension (library) · Role↔dimension saved
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
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)

Library artifacts (this run)

Kind Detail DB id
canonical_skill_proposed Dataproc | type=Cloud Platforms subtype=general nature=PLATFORM lifespan=MULTI_YEAR
canonical_skill_proposed Data Fusion | type=Data Engineering Tools subtype=general nature=TOOL lifespan=MULTI_YEAR
canonical_skill_proposed Cloud SQL | type=Cloud Platforms subtype=general nature=PLATFORM lifespan=MULTI_YEAR
canonical_skill_proposed Teradata | type=Databases subtype=general nature=TOOL lifespan=MULTI_YEAR
canonical_skill_proposed Unix | type=Operating Systems subtype=general nature=CONCEPT lifespan=EVERGREEN
canonical_skill_proposed ETL | type=Data Engineering Tools subtype=general nature=PRACTICE lifespan=MULTI_YEAR
canonical_skill_proposed Ab Initio | type=Data Engineering Tools subtype=general nature=TOOL lifespan=MULTI_YEAR
canonical_skill_proposed ODI | type=Data Engineering Tools subtype=general nature=TOOL lifespan=MULTI_YEAR
nano JD Parser — gpt-4.1-nano click to toggle
RoleData Engineer
CompanyVOIS (Vodafone Intelligent Solutions)
Experience2 to 4 years of experience
DomainTelecommunications
Location
JD type pass
Show raw JSON
{
  "JD_type": "pass",
  "about_company": {
    "source_marker": {
      "first_5_words": "VOIS (Vodafone Intelligent Solutions) is",
      "last_5_words": "teams in Czech Republic, Italy, Greece,"
    },
    "text": "VOIS (Vodafone Intelligent Solutions) is a strategic arm of Vodafone Group Plc, creating value for customers by delivering intelligent solutions through Talent, Technology \u0026 Transformation.\n\nAs the largest shared services organisation in the global telco industry with 30,000 FTE, our portfolio of next-generation solutions and services are designed in partnership with customers across Vodafone Group, local markets, and partner markets to simplify and drive growth. With our strategic partner Accenture, we work alongside our Vodafone customers, other Telco and tech companies to drive transformation, meet the challenges of our industry and ensure we stay relevant and resilient. This partnership is a unique, industry-first model which brings together the best of in-house and 3rd party capability.\n\nWe work with customers across 28 countries from 10 VOIS locations: Albania, Egypt, Hungary, India, Romania, Spain, Turkey, UK, Germany, Ireland, and with a network of teams in Czech Republic, Italy, Greece, and Portugal.",
    "word_count": 164
  },
  "certifications": [],
  "company_name": "VOIS (Vodafone Intelligent Solutions)",
  "ctc": null,
  "domain": {
    "primary": {
      "aliases": [
        "Telco",
        "Telecom"
      ],
      "domain": "Telecommunications"
    },
    "secondary": null
  },
  "education": [],
  "experience": {
    "max": 4,
    "min": 2,
    "raw": "2 to 4 years of experience"
  },
  "job_locations": [
    {
      "aliases": [],
      "city": null,
      "country": null,
      "state": null,
      "work_mode": null
    }
  ],
  "role": "Data Engineer",
  "role_aliases": [
    "Data Engineer",
    "Data Developer",
    "ETL Developer"
  ],
  "role_archetype": "Data",
  "roles_and_responsibilities": [
    {
      "bullet_count": 7,
      "heading": "What You\u2019ll Do",
      "heading_was_present": true,
      "source_marker": {
        "first_5_words": "\u2022 Design, develop, test, and",
        "last_5_words": "and troubleshoot data workflows and"
      },
      "text": "\u2022 Design, develop, test, and maintain scalable data pipelines and software systems.\n\u2022 Collaborate with cross-functional teams to gather and understand data requirements.\n\u2022 Implement ETL processes using tools such as Ab Initio or ODI.\n\u2022 Work with GCP services including BigQuery, Dataproc, Data Fusion, and Cloud SQL.\n\u2022 Write and optimise SQL queries for data extraction and transformation.\n\u2022 Ensure data quality, integrity, and performance across systems.\n\u2022 Monitor and troubleshoot data workflows and system issues.",
      "word_count": 66
    },
    {
      "bullet_count": 8,
      "heading": "Who You Are",
      "heading_was_present": true,
      "source_marker": {
        "first_5_words": "\u2022 2-4 years of experience in",
        "last_5_words": "and proactive in dynamic environments."
      },
      "text": "\u2022 2-4 years of experience in data engineering or related roles.\n\u2022 Proficient in GCP services: BigQuery, Dataproc, Data Fusion, and Cloud SQL.\n\u2022 Hands-on experience with ETL tools such as Ab Initio or ODI.\n\u2022 Strong knowledge of Unix and SQL/Teradata.\n\u2022 Exposure to Python is a plus.\n\u2022 Strong problem-solving skills and attention to detail.\n\u2022 Effective communicator and team collaborator.\n\u2022 Adaptable and proactive in dynamic environments.",
      "word_count": 80
    }
  ],
  "urls": [
    {
      "type": "linkedin",
      "url": "https://www.linkedin.com/company/vois/"
    },
    {
      "type": "facebook",
      "url": "https://www.facebook.com/voisglobal"
    },
    {
      "type": "instagram",
      "url": "https://www.instagram.com/voisglobal/"
    },
    {
      "type": "other",
      "url": "https://lnkd.in/dpkrcvR2"
    }
  ]
}
API 1 — extract-from-jd click to toggle
{
  "final_skills": [
    {
      "is_primary": true,
      "skill_name": "GCP"
    },
    {
      "is_primary": true,
      "skill_name": "BigQuery"
    },
    {
      "is_primary": true,
      "skill_name": "Dataproc"
    },
    {
      "is_primary": true,
      "skill_name": "Data Fusion"
    },
    {
      "is_primary": true,
      "skill_name": "Cloud SQL"
    },
    {
      "is_primary": true,
      "skill_name": "SQL"
    },
    {
      "is_primary": true,
      "skill_name": "Teradata"
    },
    {
      "is_primary": true,
      "skill_name": "Unix"
    },
    {
      "is_primary": false,
      "skill_name": "Python"
    },
    {
      "is_primary": true,
      "skill_name": "ETL"
    },
    {
      "is_primary": false,
      "skill_name": "Ab Initio"
    },
    {
      "is_primary": false,
      "skill_name": "ODI"
    }
  ],
  "jd_role": {
    "display_name": "Data Engineer",
    "rationale": null,
    "role_aliases": [
      "Data Engineer",
      "Data Developer",
      "ETL Developer"
    ],
    "role_archetype": "Data",
    "slug": ""
  },
  "nano_parsed": {
    "JD_type": "pass",
    "about_company": {
      "source_marker": {
        "first_5_words": "VOIS (Vodafone Intelligent Solutions) is",
        "last_5_words": "teams in Czech Republic, Italy, Greece,"
      },
      "text": "VOIS (Vodafone Intelligent Solutions) is a strategic arm of Vodafone Group Plc, creating value for customers by delivering intelligent solutions through Talent, Technology \u0026 Transformation.\n\nAs the largest shared services organisation in the global telco industry with 30,000 FTE, our portfolio of next-generation solutions and services are designed in partnership with customers across Vodafone Group, local markets, and partner markets to simplify and drive growth. With our strategic partner Accenture, we work alongside our Vodafone customers, other Telco and tech companies to drive transformation, meet the challenges of our industry and ensure we stay relevant and resilient. This partnership is a unique, industry-first model which brings together the best of in-house and 3rd party capability.\n\nWe work with customers across 28 countries from 10 VOIS locations: Albania, Egypt, Hungary, India, Romania, Spain, Turkey, UK, Germany, Ireland, and with a network of teams in Czech Republic, Italy, Greece, and Portugal.",
      "word_count": 164
    },
    "certifications": [],
    "company_name": "VOIS (Vodafone Intelligent Solutions)",
    "ctc": null,
    "domain": {
      "primary": {
        "aliases": [
          "Telco",
          "Telecom"
        ],
        "domain": "Telecommunications"
      },
      "secondary": null
    },
    "education": [],
    "experience": {
      "max": 4,
      "min": 2,
      "raw": "2 to 4 years of experience"
    },
    "job_locations": [
      {
        "aliases": [],
        "city": null,
        "country": null,
        "state": null,
        "work_mode": null
      }
    ],
    "role": "Data Engineer",
    "role_aliases": [
      "Data Engineer",
      "Data Developer",
      "ETL Developer"
    ],
    "role_archetype": "Data",
    "roles_and_responsibilities": [
      {
        "bullet_count": 7,
        "heading": "What You\u2019ll Do",
        "heading_was_present": true,
        "source_marker": {
          "first_5_words": "\u2022 Design, develop, test, and",
          "last_5_words": "and troubleshoot data workflows and"
        },
        "text": "\u2022 Design, develop, test, and maintain scalable data pipelines and software systems.\n\u2022 Collaborate with cross-functional teams to gather and understand data requirements.\n\u2022 Implement ETL processes using tools such as Ab Initio or ODI.\n\u2022 Work with GCP services including BigQuery, Dataproc, Data Fusion, and Cloud SQL.\n\u2022 Write and optimise SQL queries for data extraction and transformation.\n\u2022 Ensure data quality, integrity, and performance across systems.\n\u2022 Monitor and troubleshoot data workflows and system issues.",
        "word_count": 66
      },
      {
        "bullet_count": 8,
        "heading": "Who You Are",
        "heading_was_present": true,
        "source_marker": {
          "first_5_words": "\u2022 2-4 years of experience in",
          "last_5_words": "and proactive in dynamic environments."
        },
        "text": "\u2022 2-4 years of experience in data engineering or related roles.\n\u2022 Proficient in GCP services: BigQuery, Dataproc, Data Fusion, and Cloud SQL.\n\u2022 Hands-on experience with ETL tools such as Ab Initio or ODI.\n\u2022 Strong knowledge of Unix and SQL/Teradata.\n\u2022 Exposure to Python is a plus.\n\u2022 Strong problem-solving skills and attention to detail.\n\u2022 Effective communicator and team collaborator.\n\u2022 Adaptable and proactive in dynamic environments.",
        "word_count": 80
      }
    ],
    "urls": [
      {
        "type": "linkedin",
        "url": "https://www.linkedin.com/company/vois/"
      },
      {
        "type": "facebook",
        "url": "https://www.facebook.com/voisglobal"
      },
      {
        "type": "instagram",
        "url": "https://www.instagram.com/voisglobal/"
      },
      {
        "type": "other",
        "url": "https://lnkd.in/dpkrcvR2"
      }
    ]
  },
  "rejected": false,
  "rejection_reason": null,
  "run_id": "d8bed4ec-2eeb-4231-90e3-06c79590b876",
  "stage3_signals": {
    "alias_found": true,
    "alias_match_roles": [
      {
        "display_name": "Data Engineer",
        "kra_matches": null,
        "matched_count": null,
        "matched_skills": null,
        "role_id": 2,
        "score": 1.0,
        "slug": "data-engineer",
        "total_count": null
      }
    ],
    "kra_match_roles": [
      {
        "display_name": "Data Engineer",
        "kra_matches": [
          {
            "kra_text": "Works with data analysts, data scientists, and business stakeholders to define data models, ingestion schedules, and data delivery requirements.",
            "sentence": "Collaborate with cross-functional teams to gather and understand data requirements.",
            "similarity": 0.6546
          },
          {
            "kra_text": "Implements data quality validation rules, reconciliation checks, and anomaly detection to ensure data completeness, accuracy, and consistency.",
            "sentence": "Ensure data quality, integrity, and performance across systems.",
            "similarity": 0.6463
          },
          {
            "kra_text": "Monitors pipeline health, SLA breach alerts, and job failure notifications, and performs root cause analysis for data pipeline incidents.",
            "sentence": "Monitor and troubleshoot data workflows and system issues.",
            "similarity": 0.5921
          }
        ],
        "matched_count": null,
        "matched_skills": null,
        "role_id": 2,
        "score": 0.631,
        "slug": "data-engineer",
        "total_count": null
      },
      {
        "display_name": "Fullstack Developer",
        "kra_matches": [
          {
            "kra_text": "Designs and queries relational databases like PostgreSQL and document stores like MongoDB, writing migrations, indexes, and optimized queries.",
            "sentence": "Write and optimise SQL queries for data extraction and transformation.",
            "similarity": 0.5698
          },
          {
            "kra_text": "Designs and queries relational databases like PostgreSQL and document stores like MongoDB, writing migrations, indexes, and optimized queries.",
            "sentence": "Design, develop, test, and maintain scalable data pipelines and software systems.",
            "similarity": 0.5371
          },
          {
            "kra_text": "Debugs full-stack issues that span frontend rendering, API behavior, database queries, and infrastructure configuration to identify root causes.",
            "sentence": "Monitor and troubleshoot data workflows and system issues.",
            "similarity": 0.4695
          }
        ],
        "matched_count": null,
        "matched_skills": null,
        "role_id": 15,
        "score": 0.5255,
        "slug": "full-stack-engineer",
        "total_count": null
      },
      {
        "display_name": "MLOps Engineer",
        "kra_matches": [
          {
            "kra_text": "Validates model performance benchmarks, data schema contracts, and system integration health before signing off on production release readiness.",
            "sentence": "Ensure data quality, integrity, and performance across systems.",
            "similarity": 0.5817
          },
          {
            "kra_text": "Sets up model monitoring dashboards, data drift detection, prediction performance tracking, and alert routing for production ML systems.",
            "sentence": "Monitor and troubleshoot data workflows and system issues.",
            "similarity": 0.5114
          },
          {
            "kra_text": "Coordinates model promotion workflows across development, staging, and production environments including integration testing and data contract validation.",
            "sentence": "Design, develop, test, and maintain scalable data pipelines and software systems.",
            "similarity": 0.4437
          }
        ],
        "matched_count": null,
        "matched_skills": null,
        "role_id": 16,
        "score": 0.5123,
        "slug": "ml-ops-engineer",
        "total_count": null
      },
      {
        "display_name": "ML Engineer",
        "kra_matches": [
          {
            "kra_text": "Monitors production model behavior for data drift, concept drift, and prediction performance degradation using monitoring dashboards and alerting.",
            "sentence": "Monitor and troubleshoot data workflows and system issues.",
            "similarity": 0.5672
          },
          {
            "kra_text": "Prepares, cleans, and transforms training datasets, manages feature stores, and builds feature engineering pipelines for model training.",
            "sentence": "Design, develop, test, and maintain scalable data pipelines and software systems.",
            "similarity": 0.4976
          },
          {
            "kra_text": "Translates product requirements into machine learning system specifications including feature definitions, model architecture choices, and success metric definitions.",
            "sentence": "Collaborate with cross-functional teams to gather and understand data requirements.",
            "similarity": 0.4684
          }
        ],
        "matched_count": null,
        "matched_skills": null,
        "role_id": 3,
        "score": 0.511,
        "slug": "ml-engineer",
        "total_count": null
      },
      {
        "display_name": "DevOps Engineer",
        "kra_matches": [
          {
            "kra_text": "Monitors CI/CD pipeline reliability, identifies bottlenecks in delivery workflows, and improves deployment frequency, lead time, and failure recovery rate.",
            "sentence": "Monitor and troubleshoot data workflows and system issues.",
            "similarity": 0.5725
          },
          {
            "kra_text": "Collaborates with development teams to improve build processes, reduce deployment friction, containerize applications, and adopt DevOps best practices.",
            "sentence": "Design, develop, test, and maintain scalable data pipelines and software systems.",
            "similarity": 0.4878
          },
          {
            "kra_text": "Provisions and manages cloud infrastructure on AWS, Azure, or GCP using Terraform or CloudFormation to enforce infrastructure-as-code standards.",
            "sentence": "Work with GCP services including BigQuery, Dataproc, Data Fusion, and Cloud SQL.",
            "similarity": 0.4516
          }
        ],
        "matched_count": null,
        "matched_skills": null,
        "role_id": 10,
        "score": 0.504,
        "slug": "devops-engineer",
        "total_count": null
      }
    ],
    "skill_match_roles": [
      {
        "display_name": "Data Engineer",
        "kra_matches": null,
        "matched_count": 3,
        "matched_skills": [
          "BigQuery",
          "GCP",
          "SQL"
        ],
        "role_id": 2,
        "score": 0.3333,
        "slug": "data-engineer",
        "total_count": 9
      },
      {
        "display_name": "ML Engineer",
        "kra_matches": null,
        "matched_count": 1,
        "matched_skills": [
          "GCP"
        ],
        "role_id": 3,
        "score": 0.1111,
        "slug": "ml-engineer",
        "total_count": 9
      },
      {
        "display_name": "Cyber Security Engineer",
        "kra_matches": null,
        "matched_count": 1,
        "matched_skills": [
          "GCP"
        ],
        "role_id": 5,
        "score": 0.1111,
        "slug": "cybersecurity-engineer",
        "total_count": 9
      },
      {
        "display_name": "Cloud Architect",
        "kra_matches": null,
        "matched_count": 1,
        "matched_skills": [
          "GCP"
        ],
        "role_id": 9,
        "score": 0.1111,
        "slug": "cloud-architect",
        "total_count": 9
      },
      {
        "display_name": "Backend Developer",
        "kra_matches": null,
        "matched_count": 1,
        "matched_skills": [
          "GCP"
        ],
        "role_id": 1,
        "score": 0.1111,
        "slug": "backend-engineer",
        "total_count": 9
      }
    ]
  },
  "stage4_decision": {
    "alias_collision_detected": false,
    "case": "A",
    "chosen_role": {
      "display_name": "Data Engineer",
      "kra_matches": null,
      "matched_count": null,
      "matched_skills": null,
      "role_id": 2,
      "score": 1.0,
      "slug": "data-engineer",
      "total_count": null
    },
    "confidence": 1.0,
    "is_new_role": false,
    "llm2_fired": false,
    "llm2_reasoning": null,
    "matched_dimensions": [],
    "matched_kras": [],
    "matched_skills": [],
    "new_role_display_name": null,
    "new_role_slug": null,
    "queued": false,
    "reasoning": "Exact alias hit on data-engineer (1.0) \u2014 no other alias at this confidence; skill_top data-engineer 0.33 does not contradict",
    "sub_role": null
  },
  "stage5_updates": {
    "centroid_n_after": 268,
    "centroid_updated": true,
    "collision_log_id": null,
    "new_kra_attached": null,
    "new_skills_attached": [
      {
        "is_primary": true,
        "queue_id": 13346,
        "role_display_name": "Data Engineer",
        "role_slug": "data-engineer",
        "skill_name": "Dataproc",
        "status": "pending"
      },
      {
        "is_primary": true,
        "queue_id": 13347,
        "role_display_name": "Data Engineer",
        "role_slug": "data-engineer",
        "skill_name": "Data Fusion",
        "status": "pending"
      },
      {
        "is_primary": true,
        "queue_id": 13348,
        "role_display_name": "Data Engineer",
        "role_slug": "data-engineer",
        "skill_name": "Cloud SQL",
        "status": "pending"
      },
      {
        "is_primary": true,
        "queue_id": 13349,
        "role_display_name": "Data Engineer",
        "role_slug": "data-engineer",
        "skill_name": "Teradata",
        "status": "pending"
      },
      {
        "is_primary": true,
        "queue_id": 13350,
        "role_display_name": "Data Engineer",
        "role_slug": "data-engineer",
        "skill_name": "Unix",
        "status": "pending"
      },
      {
        "is_primary": true,
        "queue_id": 13351,
        "role_display_name": "Data Engineer",
        "role_slug": "data-engineer",
        "skill_name": "ETL",
        "status": "pending"
      },
      {
        "is_primary": false,
        "queue_id": 13352,
        "role_display_name": "Data Engineer",
        "role_slug": "data-engineer",
        "skill_name": "Ab Initio",
        "status": "pending"
      },
      {
        "is_primary": false,
        "queue_id": 13353,
        "role_display_name": "Data Engineer",
        "role_slug": "data-engineer",
        "skill_name": "ODI",
        "status": "pending"
      }
    ],
    "queue_entry_id": null,
    "v3_pipeline_triggered": false,
    "v3_role_slug": null,
    "v3_run_id": null
  }
}
API 2 — extract-details
{
  "alias_matches": [
    {
      "alias_persist_skipped_reason": "alias_text already exists for this canonical skill",
      "alias_persisted": false,
      "existing_alias_id": 405,
      "existing_alias_text": "GCP",
      "input_term": "GCP",
      "matched_canonical": {
        "category_id": 9,
        "display_name": "GCP",
        "id": 186,
        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "PLATFORM",
        "slug": "gcp",
        "sub_category_id": 46,
        "typical_lifespan": "EVERGREEN",
        "volatility": "STABLE"
      },
      "matched_via": "alias"
    },
    {
      "alias_persist_skipped_reason": "alias_text already exists for this canonical skill",
      "alias_persisted": false,
      "existing_alias_id": 300,
      "existing_alias_text": "BigQuery",
      "input_term": "BigQuery",
      "matched_canonical": {
        "category_id": 11,
        "display_name": "BigQuery",
        "id": 106,
        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "CLOUD_SERVICE",
        "slug": "bigquery",
        "sub_category_id": 118,
        "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": 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"
    }
  ],
  "candidate_roles": [
    {
      "display_name": ".NET Backend Developer",
      "id": 83,
      "rationale": null,
      "role_archetype": "Engineering",
      "slug": "dotnet-backend-developer",
      "source": "db"
    },
    {
      "display_name": "Backend Developer",
      "id": 1,
      "rationale": null,
      "role_archetype": "A Backend Engineer designs, builds, and maintains the server-side logic and data handling that power applications and services. They focus on implementing reliable business functionality, integrating with other systems, and ensuring the backend is scalable, maintainable, and observable.",
      "slug": "backend-engineer",
      "source": "db"
    },
    {
      "display_name": "Cyber Security Engineer",
      "id": 5,
      "rationale": null,
      "role_archetype": null,
      "slug": "cybersecurity-engineer",
      "source": "db"
    },
    {
      "display_name": "Data Engineer",
      "id": 2,
      "rationale": null,
      "role_archetype": null,
      "slug": "data-engineer",
      "source": "db"
    },
    {
      "display_name": "DevOps Engineer",
      "id": 10,
      "rationale": null,
      "role_archetype": null,
      "slug": "devops-engineer",
      "source": "db"
    },
    {
      "display_name": "Fullstack Developer",
      "id": 15,
      "rationale": null,
      "role_archetype": null,
      "slug": "full-stack-engineer",
      "source": "db"
    },
    {
      "display_name": "Go Backend Developer",
      "id": 81,
      "rationale": null,
      "role_archetype": "Engineering",
      "slug": "go-backend-developer",
      "source": "db"
    },
    {
      "display_name": "Java Backend Developer",
      "id": 79,
      "rationale": null,
      "role_archetype": "Engineering",
      "slug": "java-backend-developer",
      "source": "db"
    },
    {
      "display_name": "Kotlin Backend Developer",
      "id": 84,
      "rationale": null,
      "role_archetype": "Engineering",
      "slug": "kotlin-server-backend-developer",
      "source": "db"
    },
    {
      "display_name": "ML Engineer",
      "id": 3,
      "rationale": null,
      "role_archetype": null,
      "slug": "ml-engineer",
      "source": "db"
    },
    {
      "display_name": "MLOps Engineer",
      "id": 16,
      "rationale": null,
      "role_archetype": null,
      "slug": "ml-ops-engineer",
      "source": "db"
    },
    {
      "display_name": "Node.js Backend Developer",
      "id": 82,
      "rationale": null,
      "role_archetype": "Engineering",
      "slug": "node-backend-developer",
      "source": "db"
    },
    {
      "display_name": "Python Backend Developer",
      "id": 80,
      "rationale": null,
      "role_archetype": "Engineering",
      "slug": "python-backend-developer",
      "source": "db"
    },
    {
      "display_name": "Scala Backend Developer",
      "id": 87,
      "rationale": null,
      "role_archetype": "Engineering",
      "slug": "scala-backend-developer",
      "source": "db"
    },
    {
      "display_name": "AI Engineer",
      "id": 13,
      "rationale": null,
      "role_archetype": null,
      "slug": "ai-engineer",
      "source": "db"
    },
    {
      "display_name": "Cloud Architect",
      "id": 9,
      "rationale": null,
      "role_archetype": null,
      "slug": "cloud-architect",
      "source": "db"
    },
    {
      "display_name": "Cloud Security Engineer",
      "id": 23,
      "rationale": null,
      "role_archetype": null,
      "slug": "cloud-security-engineer",
      "source": "db"
    },
    {
      "display_name": "Pega Developer",
      "id": 24,
      "rationale": null,
      "role_archetype": null,
      "slug": "pega-developer",
      "source": "db"
    },
    {
      "display_name": "Engineering Manager",
      "id": 121,
      "rationale": null,
      "role_archetype": null,
      "slug": "engineering-manager",
      "source": "db"
    },
    {
      "display_name": "Fullstack Developer",
      "id": 435,
      "rationale": null,
      "role_archetype": "Engineering",
      "slug": "fullstack-developer",
      "source": "db"
    },
    {
      "display_name": "AR/VR Engineer",
      "id": 8,
      "rationale": null,
      "role_archetype": null,
      "slug": "ar-vr-engineer",
      "source": "db"
    }
  ],
  "chosen_role": {
    "display_name": "Data Engineer",
    "id": 2,
    "rationale": "Exact alias hit on data-engineer (1.0) \u2014 no other alias at this confidence; skill_top data-engineer 0.33 does not contradict",
    "role_archetype": null,
    "slug": "data-engineer",
    "source": "db"
  },
  "dimensions": [
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "Cloud Platforms",
        "id": 20,
        "rationale": "Underlying cloud providers that host the managed services or infrastructure used by the role, such as AWS, Azure, and GCP.",
        "slug": "cloud-platforms",
        "source": "db"
      },
      "input_skill": "GCP",
      "llm_role": null,
      "roles_from_db": [
        {
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      "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": "Dataproc",
      "matched_via": null,
      "new_alias_persisted": false,
      "new_alias_text": null,
      "new_skill_meta": {
        "derived": {
          "category": "Cloud Platforms",
          "skill_nature": "PLATFORM",
          "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": "dataproc",
        "split_log": [],
        "typed": null,
        "warnings": []
      },
      "source_tag": "llm",
      "was_in_llm_skills": true
    },
    {
      "aliases_in_db": [],
      "canonical": null,
      "dimensions": [],
      "input_skill": "Data Fusion",
      "matched_via": null,
      "new_alias_persisted": false,
      "new_alias_text": null,
      "new_skill_meta": {
        "derived": {
          "category": "Data Engineering Tools",
          "skill_nature": "TOOL",
          "sub_category": "general",
          "typical_lifespan": "MULTI_YEAR",
          "version_strategy": "UNVERSIONED",
          "volatility": "MEDIUM"
        },
        "enrichment": null,
        "keep_log": [],
        "locked_dimensions": [],
        "merge_log": [],
        "placed": null,
        "relationships": null,
        "skill_id": "data-fusion",
        "split_log": [],
        "typed": null,
        "warnings": []
      },
      "source_tag": "llm",
      "was_in_llm_skills": true
    },
    {
      "aliases_in_db": [],
      "canonical": null,
      "dimensions": [],
      "input_skill": "Cloud SQL",
      "matched_via": null,
      "new_alias_persisted": false,
      "new_alias_text": null,
      "new_skill_meta": {
        "derived": {
          "category": "Cloud Platforms",
          "skill_nature": "PLATFORM",
          "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": "cloud-sql",
        "split_log": [],
        "typed": null,
        "warnings": []
      },
      "source_tag": "llm",
      "was_in_llm_skills": true
    },
    {
      "aliases_in_db": [
        {
          "alias_text": "SQL",
          "alias_type": "CANONICAL",
          "id": 271,
          "is_primary": true,
          "match_strategy": "CASE_INSENSITIVE"
        }
      ],
      "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"
      },
      "dimensions": [
        {
          "dimension": {
            "difficulty_hint": "well_known",
            "display_name": "Pega Programming Languages \u0026 DSLs",
            "id": 267,
            "rationale": "Programming languages and domain-specific languages used in Pega development.",
            "slug": "pega-programming-languages-dsls",
            "source": "db"
          },
          "input_skill": "SQL",
          "llm_role": null,
          "roles_from_db": [
            {
              "display_name": "Pega Developer",
              "id": 24,
              "rationale": null,
              "role_archetype": null,
              "slug": "pega-developer",
              "source": "db"
            }
          ]
        },
        {
          "dimension": {
            "difficulty_hint": "well_known",
            "display_name": "Programming Languages \u0026 DSLs",
            "id": 475,
            "rationale": "Oversee and guide the selection and effective use of programming and domain\u2010specific languages in software projects.",
            "slug": "programming-languages-dsls",
            "source": "db"
          },
          "input_skill": "SQL",
          "llm_role": null,
          "roles_from_db": [
            {
              "display_name": "Engineering Manager",
              "id": 121,
              "rationale": null,
              "role_archetype": null,
              "slug": "engineering-manager",
              "source": "db"
            }
          ]
        },
        {
          "dimension": {
            "difficulty_hint": "well_known",
            "display_name": "Programming Languages for Data Work",
            "id": 21,
            "rationale": "Languages used to implement data pipelines, transformations, and operational glue. This is the primary coding surface for building ingestion, enrichment, and automation logic in data engineering.",
            "slug": "programming-languages-for-data-work",
            "source": "db"
          },
          "input_skill": "SQL",
          "llm_role": null,
          "roles_from_db": [
            {
              "display_name": "Data Engineer",
              "id": 2,
              "rationale": null,
              "role_archetype": null,
              "slug": "data-engineer",
              "source": "db"
            }
          ]
        }
      ],
      "input_skill": "SQL",
      "matched_via": "alias",
      "new_alias_persisted": false,
      "new_alias_text": null,
      "new_skill_meta": null,
      "source_tag": "db",
      "was_in_llm_skills": true
    },
    {
      "aliases_in_db": [],
      "canonical": null,
      "dimensions": [],
      "input_skill": "Teradata",
      "matched_via": null,
      "new_alias_persisted": false,
      "new_alias_text": null,
      "new_skill_meta": {
        "derived": {
          "category": "Databases",
          "skill_nature": "TOOL",
          "sub_category": "general",
          "typical_lifespan": "MULTI_YEAR",
          "version_strategy": "UNVERSIONED",
          "volatility": "MEDIUM"
        },
        "enrichment": null,
        "keep_log": [],
        "locked_dimensions": [],
        "merge_log": [],
        "placed": null,
        "relationships": null,
        "skill_id": "teradata",
        "split_log": [],
        "typed": null,
        "warnings": []
      },
      "source_tag": "llm",
      "was_in_llm_skills": true
    },
    {
      "aliases_in_db": [],
      "canonical": null,
      "dimensions": [],
      "input_skill": "Unix",
      "matched_via": null,
      "new_alias_persisted": false,
      "new_alias_text": null,
      "new_skill_meta": {
        "derived": {
          "category": "Operating Systems",
          "skill_nature": "CONCEPT",
          "sub_category": "general",
          "typical_lifespan": "EVERGREEN",
          "version_strategy": "UNVERSIONED",
          "volatility": "STABLE"
        },
        "enrichment": null,
        "keep_log": [],
        "locked_dimensions": [],
        "merge_log": [],
        "placed": null,
        "relationships": null,
        "skill_id": "unix",
        "split_log": [],
        "typed": null,
        "warnings": []
      },
      "source_tag": "llm",
      "was_in_llm_skills": true
    },
    {
      "aliases_in_db": [
        {
          "alias_text": "Python",
          "alias_type": "CANONICAL",
          "id": 67,
          "is_primary": true,
          "match_strategy": "CASE_INSENSITIVE"
        },
        {
          "alias_text": "Python 2",
          "alias_type": "VERSION",
          "id": 72,
          "is_primary": false,
          "match_strategy": "CASE_INSENSITIVE"
        },
        {
          "alias_text": "Python 2.x",
          "alias_type": "VERSION",
          "id": 74,
          "is_primary": false,
          "match_strategy": "CASE_INSENSITIVE"
        },
        {
          "alias_text": "Python 3",
          "alias_type": "VERSION",
          "id": 73,
          "is_primary": false,
          "match_strategy": "CASE_INSENSITIVE"
        },
        {
          "alias_text": "Python 3.10",
          "alias_type": "VERSION",
          "id": 76,
          "is_primary": false,
          "match_strategy": "CASE_INSENSITIVE"
        },
        {
          "alias_text": "Python 3.11",
          "alias_type": "VERSION",
          "id": 77,
          "is_primary": false,
          "match_strategy": "CASE_INSENSITIVE"
        },
        {
          "alias_text": "Python 3.12",
          "alias_type": "VERSION",
          "id": 78,
          "is_primary": false,
          "match_strategy": "CASE_INSENSITIVE"
        },
        {
          "alias_text": "Python 3.x",
          "alias_type": "VERSION",
          "id": 75,
          "is_primary": false,
          "match_strategy": "CASE_INSENSITIVE"
        },
        {
          "alias_text": "py",
          "alias_type": "VERSION",
          "id": 2183,
          "is_primary": false,
          "match_strategy": "CASE_INSENSITIVE"
        },
        {
          "alias_text": "py2",
          "alias_type": "VERSION",
          "id": 68,
          "is_primary": false,
          "match_strategy": "CASE_INSENSITIVE"
        },
        {
          "alias_text": "py3",
          "alias_type": "VERSION",
          "id": 69,
          "is_primary": false,
          "match_strategy": "CASE_INSENSITIVE"
        },
        {
          "alias_text": "python 3",
          "alias_type": "VERSION",
          "id": 2186,
          "is_primary": false,
          "match_strategy": "CASE_INSENSITIVE"
        },
        {
          "alias_text": "python 3.x",
          "alias_type": "VERSION",
          "id": 2849,
          "is_primary": false,
          "match_strategy": "CASE_INSENSITIVE"
        },
        {
          "alias_text": "python2",
          "alias_type": "VERSION",
          "id": 70,
          "is_primary": false,
          "match_strategy": "CASE_INSENSITIVE"
        },
        {
          "alias_text": "python3",
          "alias_type": "VERSION",
          "id": 71,
          "is_primary": false,
          "match_strategy": "CASE_INSENSITIVE"
        },
        {
          "alias_text": "python3.x",
          "alias_type": "VERSION",
          "id": 2848,
          "is_primary": false,
          "match_strategy": "CASE_INSENSITIVE"
        }
      ],
      "canonical": {
        "category_id": 6,
        "display_name": "Python",
        "id": 5,
        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "LANGUAGE",
        "slug": "python",
        "sub_category_id": 96,
        "typical_lifespan": "EVERGREEN",
        "volatility": "STABLE"
      },
      "dimensions": [
        {
          "dimension": {
            "difficulty_hint": "well_known",
            "display_name": "Cloud Security Scripting \u0026 DSL Languages",
            "id": 248,
            "rationale": "Proficiency in programming and domain-specific languages used to automate and script cloud security controls.",
            "slug": "cloud-security-scripting-dsl-languages",
            "source": "db"
          },
          "input_skill": "Python",
          "llm_role": null,
          "roles_from_db": [
            {
              "display_name": "Cloud Security Engineer",
              "id": 23,
              "rationale": null,
              "role_archetype": null,
              "slug": "cloud-security-engineer",
              "source": "db"
            }
          ]
        },
        {
          "dimension": {
            "difficulty_hint": "well_known",
            "display_name": "Programming Languages",
            "id": 1,
            "rationale": "Primary implementation languages used to build client and server feature code. Full stack engineers need enough fluency to move across layers and implement product behavior end to end.",
            "slug": "programming-languages",
            "source": "db"
          },
          "input_skill": "Python",
          "llm_role": null,
          "roles_from_db": [
            {
              "display_name": "Backend Developer",
              "id": 1,
              "rationale": null,
              "role_archetype": "A Backend Engineer designs, builds, and maintains the server-side logic and data handling that power applications and services. They focus on implementing reliable business functionality, integrating with other systems, and ensuring the backend is scalable, maintainable, and observable.",
              "slug": "backend-engineer",
              "source": "db"
            },
            {
              "display_name": "Fullstack Developer",
              "id": 15,
              "rationale": null,
              "role_archetype": null,
              "slug": "full-stack-engineer",
              "source": "db"
            },
            {
              "display_name": "Fullstack Developer",
              "id": 435,
              "rationale": null,
              "role_archetype": "Engineering",
              "slug": "fullstack-developer",
              "source": "db"
            }
          ]
        },
        {
          "dimension": {
            "difficulty_hint": "well_known",
            "display_name": "Programming Languages \u0026 DSLs",
            "id": 475,
            "rationale": "Oversee and guide the selection and effective use of programming and domain\u2010specific languages in software projects.",
            "slug": "programming-languages-dsls",
            "source": "db"
          },
          "input_skill": "Python",
          "llm_role": null,
          "roles_from_db": [
            {
              "display_name": "Engineering Manager",
              "id": 121,
              "rationale": null,
              "role_archetype": null,
              "slug": "engineering-manager",
              "source": "db"
            }
          ]
        },
        {
          "dimension": {
            "difficulty_hint": "well_known",
            "display_name": "Programming Languages and Scripting",
            "id": 59,
            "rationale": "Languages used to write security automation, analysis scripts, detection logic, and remediation helpers. This is the primary implementation surface for a cybersecurity engineer across tooling and response workflows.",
            "slug": "programming-languages-and-scripting",
            "source": "db"
          },
          "input_skill": "Python",
          "llm_role": null,
          "roles_from_db": [
            {
              "display_name": "Cyber Security Engineer",
              "id": 5,
              "rationale": null,
              "role_archetype": null,
              "slug": "cybersecurity-engineer",
              "source": "db"
            }
          ]
        },
        {
          "dimension": {
            "difficulty_hint": "well_known",
            "display_name": "Programming Languages for Data Work",
            "id": 21,
            "rationale": "Languages used to implement data pipelines, transformations, and operational glue. This is the primary coding surface for building ingestion, enrichment, and automation logic in data engineering.",
            "slug": "programming-languages-for-data-work",
            "source": "db"
          },
          "input_skill": "Python",
          "llm_role": null,
          "roles_from_db": [
            {
              "display_name": "Data Engineer",
              "id": 2,
              "rationale": null,
              "role_archetype": null,
              "slug": "data-engineer",
              "source": "db"
            }
          ]
        },
        {
          "dimension": {
            "difficulty_hint": "well_known",
            "display_name": "Programming Languages for ML Systems",
            "id": 39,
            "rationale": "Languages used to build training code, inference services, evaluation jobs, and ML glue code. This is the primary implementation surface for ML engineers across experimentation and productionization.",
            "slug": "programming-languages-for-ml-systems",
            "source": "db"
          },
          "input_skill": "Python",
          "llm_role": null,
          "roles_from_db": [
            {
              "display_name": "ML Engineer",
              "id": 3,
              "rationale": null,
              "role_archetype": null,
              "slug": "ml-engineer",
              "source": "db"
            },
            {
              "display_name": "MLOps Engineer",
              "id": 16,
              "rationale": null,
              "role_archetype": null,
              "slug": "ml-ops-engineer",
              "source": "db"
            }
          ]
        },
        {
          "dimension": {
            "difficulty_hint": "well_known",
            "display_name": "Programming Languages for XR",
            "id": 97,
            "rationale": "Primary implementation languages used to build immersive client features, interaction logic, and device-specific runtime behavior. This is the core coding surface for AR/VR experiences.",
            "slug": "programming-languages-for-xr",
            "source": "db"
          },
          "input_skill": "Python",
          "llm_role": null,
          "roles_from_db": [
            {
              "display_name": "AR/VR Engineer",
              "id": 8,
              "rationale": null,
              "role_archetype": null,
              "slug": "ar-vr-engineer",
              "source": "db"
            }
          ]
        },
        {
          "dimension": {
            "difficulty_hint": "well_known",
            "display_name": "Python Programming",
            "id": 290,
            "rationale": "Core Python language skills used to implement backend business logic, request handlers, integrations, and service internals. This is the primary coding surface for the role.",
            "slug": "python-programming",
            "source": "db"
          },
          "input_skill": "Python",
          "llm_role": null,
          "roles_from_db": [
            {
              "display_name": "Python Backend Developer",
              "id": 80,
              "rationale": null,
              "role_archetype": "Engineering",
              "slug": "python-backend-developer",
              "source": "db"
            }
          ]
        }
      ],
      "input_skill": "Python",
      "matched_via": "alias",
      "new_alias_persisted": false,
      "new_alias_text": null,
      "new_skill_meta": null,
      "source_tag": "db",
      "was_in_llm_skills": true
    },
    {
      "aliases_in_db": [],
      "canonical": null,
      "dimensions": [],
      "input_skill": "ETL",
      "matched_via": null,
      "new_alias_persisted": false,
      "new_alias_text": null,
      "new_skill_meta": {
        "derived": {
          "category": "Data Engineering Tools",
          "skill_nature": "PRACTICE",
          "sub_category": "general",
          "typical_lifespan": "MULTI_YEAR",
          "version_strategy": "UNVERSIONED",
          "volatility": "MEDIUM"
        },
        "enrichment": null,
        "keep_log": [],
        "locked_dimensions": [],
        "merge_log": [],
        "placed": null,
        "relationships": null,
        "skill_id": "etl",
        "split_log": [],
        "typed": null,
        "warnings": []
      },
      "source_tag": "llm",
      "was_in_llm_skills": true
    },
    {
      "aliases_in_db": [],
      "canonical": null,
      "dimensions": [],
      "input_skill": "Ab Initio",
      "matched_via": null,
      "new_alias_persisted": false,
      "new_alias_text": null,
      "new_skill_meta": {
        "derived": {
          "category": "Data Engineering Tools",
          "skill_nature": "TOOL",
          "sub_category": "general",
          "typical_lifespan": "MULTI_YEAR",
          "version_strategy": "UNVERSIONED",
          "volatility": "MEDIUM"
        },
        "enrichment": null,
        "keep_log": [],
        "locked_dimensions": [],
        "merge_log": [],
        "placed": null,
        "relationships": null,
        "skill_id": "ab-initio",
        "split_log": [],
        "typed": null,
        "warnings": []
      },
      "source_tag": "llm",
      "was_in_llm_skills": true
    },
    {
      "aliases_in_db": [],
      "canonical": null,
      "dimensions": [],
      "input_skill": "ODI",
      "matched_via": null,
      "new_alias_persisted": false,
      "new_alias_text": null,
      "new_skill_meta": {
        "derived": {
          "category": "Data Engineering Tools",
          "skill_nature": "TOOL",
          "sub_category": "general",
          "typical_lifespan": "MULTI_YEAR",
          "version_strategy": "UNVERSIONED",
          "volatility": "MEDIUM"
        },
        "enrichment": null,
        "keep_log": [],
        "locked_dimensions": [],
        "merge_log": [],
        "placed": null,
        "relationships": null,
        "skill_id": "odi",
        "split_log": [],
        "typed": null,
        "warnings": []
      },
      "source_tag": "llm",
      "was_in_llm_skills": true
    }
  ],
  "unmatched_skills": [
    "Dataproc",
    "Data Fusion",
    "Cloud SQL",
    "Teradata",
    "Unix",
    "ETL",
    "Ab Initio",
    "ODI"
  ]
}
API 3 — final-role-output
{
  "chosen_role": {
    "display_name": "Data Engineer",
    "id": 2,
    "rationale": "Exact alias hit on data-engineer (1.0) \u2014 no other alias at this confidence; skill_top data-engineer 0.33 does not contradict",
    "role_archetype": null,
    "slug": "data-engineer",
    "source": "db"
  },
  "chosen_role_resolution": "in_db",
  "final_input_skills": [
    {
      "skill": "GCP",
      "tag": "in_db"
    },
    {
      "skill": "BigQuery",
      "tag": "in_db"
    },
    {
      "skill": "Dataproc",
      "tag": "new"
    },
    {
      "skill": "Data Fusion",
      "tag": "new"
    },
    {
      "skill": "Cloud SQL",
      "tag": "new"
    },
    {
      "skill": "SQL",
      "tag": "in_db"
    },
    {
      "skill": "Teradata",
      "tag": "new"
    },
    {
      "skill": "Unix",
      "tag": "new"
    },
    {
      "skill": "Python",
      "tag": "in_db"
    },
    {
      "skill": "ETL",
      "tag": "new"
    },
    {
      "skill": "Ab Initio",
      "tag": "new"
    },
    {
      "skill": "ODI",
      "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 Platforms",
          "id": 20,
          "rationale": "Underlying cloud providers that host the managed services or infrastructure used by the role, such as AWS, Azure, and GCP.",
          "slug": "cloud-platforms",
          "source": "db"
        },
        "dimension_id": 20,
        "input_skill": "GCP",
        "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": ".NET Backend Developer",
            "id": 83,
            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "dotnet-backend-developer",
            "source": "db"
          },
          {
            "display_name": "Backend Developer",
            "id": 1,
            "rationale": null,
            "role_archetype": "A Backend Engineer designs, builds, and maintains the server-side logic and data handling that power applications and services. They focus on implementing reliable business functionality, integrating with other systems, and ensuring the backend is scalable, maintainable, and observable.",
            "slug": "backend-engineer",
            "source": "db"
          },
          {
            "display_name": "Cyber Security Engineer",
            "id": 5,
            "rationale": null,
            "role_archetype": null,
            "slug": "cybersecurity-engineer",
            "source": "db"
          },
          {
            "display_name": "Data Engineer",
            "id": 2,
            "rationale": null,
            "role_archetype": null,
            "slug": "data-engineer",
            "source": "db"
          },
          {
            "display_name": "DevOps Engineer",
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            "rationale": null,
            "role_archetype": null,
            "slug": "devops-engineer",
            "source": "db"
          },
          {
            "display_name": "Fullstack Developer",
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            "rationale": null,
            "role_archetype": null,
            "slug": "full-stack-engineer",
            "source": "db"
          },
          {
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            "rationale": null,
            "role_archetype": "Engineering",
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            "source": "db"
          },
          {
            "display_name": "Java Backend Developer",
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            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "java-backend-developer",
            "source": "db"
          },
          {
            "display_name": "Kotlin Backend Developer",
            "id": 84,
            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "kotlin-server-backend-developer",
            "source": "db"
          },
          {
            "display_name": "ML Engineer",
            "id": 3,
            "rationale": null,
            "role_archetype": null,
            "slug": "ml-engineer",
            "source": "db"
          },
          {
            "display_name": "MLOps Engineer",
            "id": 16,
            "rationale": null,
            "role_archetype": null,
            "slug": "ml-ops-engineer",
            "source": "db"
          },
          {
            "display_name": "Node.js Backend Developer",
            "id": 82,
            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "node-backend-developer",
            "source": "db"
          },
          {
            "display_name": "Python Backend Developer",
            "id": 80,
            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "python-backend-developer",
            "source": "db"
          },
          {
            "display_name": "Scala Backend Developer",
            "id": 87,
            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "scala-backend-developer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 186,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 2,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Cloud Platforms for AI Deployment",
          "id": 211,
          "rationale": "Major cloud services that provide infrastructure and managed services for AI workloads.",
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          "source": "db"
        },
        "dimension_id": 211,
        "input_skill": "GCP",
        "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": "AI Engineer",
            "id": 13,
            "rationale": null,
            "role_archetype": null,
            "slug": "ai-engineer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 186,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 2,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Cloud Provider Platforms",
          "id": 131,
          "rationale": "Major cloud platforms and their core service ecosystems used to design target-state architectures, choose deployment boundaries, and evaluate managed capabilities. This is the primary substrate for cloud architecture decisions.",
          "slug": "cloud-provider-platforms",
          "source": "db"
        },
        "dimension_id": 131,
        "input_skill": "GCP",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": "Cloud Architect",
            "id": 9,
            "rationale": null,
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            "slug": "cloud-architect",
            "source": "db"
          },
          {
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            "rationale": null,
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            "slug": "cloud-security-engineer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 186,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 2,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Cloud Security Posture Tools",
          "id": 64,
          "rationale": "Cloud-native security platforms used to assess misconfiguration, workload exposure, and cloud control coverage. This dimension includes the major CNAPP/CSPM/CWPP vendors and cloud security services the role reviews and tunes.",
          "slug": "cloud-security-posture-tools",
          "source": "db"
        },
        "dimension_id": 64,
        "input_skill": "GCP",
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        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": "Cloud Security Engineer",
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            "rationale": null,
            "role_archetype": null,
            "slug": "cloud-security-engineer",
            "source": "db"
          },
          {
            "display_name": "Cyber Security Engineer",
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            "rationale": null,
            "role_archetype": null,
            "slug": "cybersecurity-engineer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 186,
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        "skipped_reason": null
      },
      {
        "chosen_role_id": 2,
        "dimension": {
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          "rationale": "Managed analytical storage and compute platforms used for curated datasets, reporting, and downstream analytics. These systems are central to data modeling, performance tuning, and cost-aware query design.",
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          "source": "db"
        },
        "dimension_id": 22,
        "input_skill": "BigQuery",
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        "matched_chosen_role": true,
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        "roles_from_db": [
          {
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            "slug": "data-engineer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 106,
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        "skipped_reason": null
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      {
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          "display_name": "Pega Programming Languages \u0026 DSLs",
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          "source": "db"
        },
        "dimension_id": 267,
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        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": "Pega Developer",
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            "slug": "pega-developer",
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          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 101,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 2,
        "dimension": {
          "difficulty_hint": "well_known",
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          "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": [
          {
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        ],
        "skill_dimension_saved": true,
        "skill_id": 101,
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        "skipped_reason": null
      },
      {
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        "dimension": {
          "difficulty_hint": "well_known",
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          "rationale": "Languages used to implement data pipelines, transformations, and operational glue. This is the primary coding surface for building ingestion, enrichment, and automation logic in data engineering.",
          "slug": "programming-languages-for-data-work",
          "source": "db"
        },
        "dimension_id": 21,
        "input_skill": "SQL",
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        "roles_from_db": [
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        "skill_dimension_saved": true,
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        },
        "dimension_id": 248,
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        "roles_from_db": [
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        "dimension": {
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          "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.",
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          "source": "db"
        },
        "dimension_id": 1,
        "input_skill": "Python",
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        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
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        "roles_from_db": [
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          },
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            "rationale": null,
            "role_archetype": null,
            "slug": "full-stack-engineer",
            "source": "db"
          },
          {
            "display_name": "Fullstack Developer",
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            "rationale": null,
            "role_archetype": "Engineering",
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            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 5,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
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        "dimension": {
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          "rationale": "Oversee and guide the selection and effective use of programming and domain\u2010specific languages in software projects.",
          "slug": "programming-languages-dsls",
          "source": "db"
        },
        "dimension_id": 475,
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        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": "Engineering Manager",
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        ],
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        "skipped_reason": null
      },
      {
        "chosen_role_id": 2,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Programming Languages and Scripting",
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          "rationale": "Languages used to write security automation, analysis scripts, detection logic, and remediation helpers. This is the primary implementation surface for a cybersecurity engineer across tooling and response workflows.",
          "slug": "programming-languages-and-scripting",
          "source": "db"
        },
        "dimension_id": 59,
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        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": "Cyber Security Engineer",
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            "slug": "cybersecurity-engineer",
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        ],
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        "skill_id": 5,
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        "skipped_reason": null
      },
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        "dimension": {
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          "slug": "programming-languages-for-data-work",
          "source": "db"
        },
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        "matched_chosen_role": true,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension saved",
        "role_dimension_saved": true,
        "roles_from_db": [
          {
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            "role_archetype": null,
            "slug": "data-engineer",
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          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 5,
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        "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,
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            "slug": "ml-ops-engineer",
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        ],
        "skill_dimension_saved": true,
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          "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",
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        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": "AR/VR Engineer",
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            "rationale": null,
            "role_archetype": null,
            "slug": "ar-vr-engineer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 5,
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        "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",
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        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": "Python Backend Developer",
            "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
      }
    ],
    "new_skills_created": 0,
    "role_dimension_saved": 0,
    "skill_dimension_saved": 0,
    "skipped": 0
  },
  "planner_output": null,
  "run_id": "d8bed4ec-2eeb-4231-90e3-06c79590b876"
}

LLM Calls

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

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