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Pipeline run

5c740f5f-a54f-4fe5-944b-7eadd2c9ad6c

Pipeline LLM cost (USD)
API 1: $0.0033 API 2: $0.0002 API 3: $0.0000 Total: $0.0035

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 · Integration and event handling
Design and implement enterprise data architecture for Data Lake/Data Warehouse/ETL solutions, deploy and integrate IBM Cloud Pak for Data/DataStage with Hadoop, and advise teams on performance tuning and best practices.
""Experience Cloud Pak for Data services and able to do integration between different services""
Tech stack maturity
Mainstream Legacy
Hadoop is an established big-data ecosystem most commonly associated with older distributed data platforms rather than cloud-native or bleeding-edge stacks.
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 (7)
Data Lake Data Warehouse ETL IBM InfoSphere Cloud Pak for Data DataStage Hadoop
Skill cluster (1 dimension groups, role-scoped)
Cross-cutting / unaligned
Data Lake Data Warehouse ETL IBM InfoSphere Cloud Pak for Data DataStage Hadoop
Show KRA description ↓
1. Designing enterprise data architecture and designing building solution for Data Lake Data Warehouse ETL solutions 2. Model and design the application data structure storage and integration 3. IBM InfoSphere Suite of products Designated Capability Expert and provide SME support 4. Enterprise application performance calibration technical guidance to project team and suggest improvements best practices and recommendations to project team 5. RFP proposal with ADM estimator and Solution Approach 1. Experience to deploy Cloud Pak for Data for clients across various platforms 2. Experience Cloud Pak for Data services and able to do integration between different services 3. Strong experience on lDataStage integration with cloud Hadoop ecosystem real time stages 1. Good communication skills and interpersonal skills 2. Should have prior experience of leading a team being cooperative, collaborative, empathetic with the team members 3. Should have strong analytical abilities and creative problem solving skills 4. Should have the ability to adapt to changes quickly

Signals

Skill data-engineer
0.14
Alias backend-engineer
1.00
KRA data-engineer
0.56

Post-classification

Centroidupdated · n=1692
Alias collision log
New-role queue
New skills captured6
New KRA capturedyes

Captured for admin review

Data Lake primary Backend Developer pending
Data Warehouse primary Backend Developer pending
ETL primary Backend Developer pending
IBM InfoSphere primary Backend Developer pending
Cloud Pak for Data primary Backend Developer pending
DataStage primary Backend Developer pending
R&R fragment (sim 0.00) Backend Developer pending

1. Designing enterprise data architecture and designing building solution for Data Lake Data Warehouse ETL solutions 2. Model and design the application data structure storage and integration 3. IBM I…

Status: completed Created: 2026-05-27T17:35:09.391635Z Updated: 2026-05-27T17:35:52.290048Z API 3 duration: 1234 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

Backend Developer

CASE A

slug: backend-engineer · id: 1 · source: db

Exact alias hit on backend-engineer (1.0) — no other alias at this confidence; skill_top data-engineer 0.14 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
2
Skipped

Job description

About Accenture: Accenture is a global professional services company with leading capabilities in digital, cloud and security. Combining unmatched experience and specialized skills across more than 40 industries, we offer Strategy and Consulting, Interactive, Technology and Operations services-all powered by the world's largest network of Advanced Technology and Intelligent Operations centers. Our 514,000 people deliver on the promise of technology and human ingenuity every day, serving clients in more than 120 countries. We embrace the power of change to create value and shared success for our clients, people, shareholders, partners and communities. Visit us at www.accenture.com  Accenture | Let there be change We embrace change to create 360-degree value www.accenture.com

Project Role :Application Developer

Project Role Description :Design, build and configure applications to meet business process and application requirements.

Management Level :8

Work Experience :8-10 years

Work location :Bengaluru

Must Have Skills :IBM Cloud Pak - Data

Good To Have Skills :No Technology Specialization

Job Requirements : 

Key Responsibilities : 1. Designing enterprise data architecture and designing building solution for Data Lake Data Warehouse ETL solutions2. Model and design the application data structure storage and integration 3. IBM InfoSphere Suite of products Designated Capability Expert and provide SME support4. Enterprise application performance calibration technical guidance to project team and suggest improvements best practices and recommendations to project team 5. RFP proposal with ADM estimator and Solution Approach

Technical Experience : 1. Experience to deploy Cloud Pak for Data for clients across various platforms 2. Experience Cloud Pak for Data services and able to do integration between different services 3. Strong experience on lDataStage integration with cloud Hadoop ecosystem real time stages

Professional Attributes : 1. Good communication skills and interpersonal skills2. Should have prior experience of leading a team being cooperative,collaborative, empathetic with the team members3. Should have strong analytical abilities and creative problem solving skills4. Should have the ability to adapt to changes quickly

Educational Qualification : B-tech or BE

15 years of full time education

Skills from this JD

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

Data Lake Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: Data Lakes id=1358 · data-lakes

Aliases — catalog

  • Data Lakes (CANONICAL)

Context tags (catalog)

AWS Lake Formation Azure Data Lake ETL big data data catalog data governance data ingestion data lakes vs data warehouses data modeling data pipelines data warehousing partitioning real-time analytics schema evolution serverless architecture

Stored enrichment (catalog DB)

Category
Architecture
Sub-category
Data Lake Architecture
Confidence
0.90
Version strategy
NOT_APPLICABLE

Maturity reasoning: Data lakes are widely listed in cloud/data platform job descriptions and are a standard architecture in AWS, Azure, and GCP ecosystems; they’re a common hiring-pipeline staple rather than a niche pattern.

Skill profile (library / DB)

Skill nature
PATTERN
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
1
Sub-category id
1025
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • Cloud Storage and Data Services Catalog dimension db id 144

    Library dimension (catalog)

    Roles linked in library: Cloud Architect

  • React Frontend Development Catalog dimension db id 96

    Library dimension (catalog)

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
Cloud Storage and Data Services
cloud-storage-and-data-services
Skipped — no persistable v3 meta for new skill
skill_not_in_db_v3_proposed
React Frontend Development
d_init_01
Skipped — no persistable v3 meta for new skill
skill_not_in_db_v3_proposed
Data Warehouse Primary New / orchestrated API 3: new canonical path (new) New / unmatched skill (orchestrated in API 2)

Skill enrichment (orchestrator / LLM)

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

Derived legacy fields
Category
Data Engineering Tools
Sub-category
general
Skill nature
CONCEPT
Volatility
STABLE
Typical lifespan
EVERGREEN
Version strategy
UNVERSIONED
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
CONCEPT
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
IBM InfoSphere 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
ETL Tools
Skill nature
TOOL
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
Cloud Pak for Data Primary New / orchestrated API 3: new canonical path (new) New / unmatched skill (orchestrated in API 2)

Skill enrichment (orchestrator / LLM)

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

Derived legacy fields
Category
Data Engineering Tools
Sub-category
Cloud Services
Skill nature
PLATFORM
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
DataStage 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
ETL Tools
Skill nature
TOOL
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
Hadoop Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: Hadoop id=1351 · hadoop

Aliases — catalog

  • Hadoop (CANONICAL)

Context tags (catalog)

Big Data Data Lake Distributed Computing ELT ETL Flume HDFS Hive Kafka MapReduce NoSQL Oozie Pig Spark Sqoop YARN

Stored enrichment (catalog DB)

Category
Framework
Sub-category
Data Processing Framework
Vendor
Apache Software Foundation
License
apache_2
Year introduced
2006
Confidence
0.90
Version strategy
NOT_APPLICABLE

Maturity reasoning: Job postings still mention Hadoop for legacy big-data stacks, but JD volume has fallen as Spark and cloud warehouses replaced MapReduce-era clusters.

Skill profile (library / DB)

Skill nature
FRAMEWORK
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
5
Sub-category id
91
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • ETL and ELT Tooling Catalog dimension db id 24

    Library dimension (catalog)

    Roles linked in library: Data Engineer

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
ETL and ELT Tooling
etl-and-elt-tooling
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)

All API 3 persistence rows

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

Skill Tag Dimension Skill↔dim Role↔dim Outcome Notes
Data Lake new
Cloud Storage and Data Services
cloud-storage-and-data-services
Skipped — no persistable v3 meta for new skill skill_not_in_db_v3_proposed
Data Lake new
React Frontend Development
d_init_01
Skipped — no persistable v3 meta for new skill skill_not_in_db_v3_proposed
Hadoop in_db
ETL and ELT Tooling
etl-and-elt-tooling
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)

Library artifacts (this run)

Kind Detail DB id
canonical_skill_proposed Data Warehouse | type=Data Engineering Tools subtype=general nature=CONCEPT lifespan=EVERGREEN
canonical_skill_proposed ETL | type=Data Engineering Tools subtype=general nature=CONCEPT lifespan=MULTI_YEAR
canonical_skill_proposed IBM InfoSphere | type=Data Engineering Tools subtype=ETL Tools nature=TOOL lifespan=MULTI_YEAR
canonical_skill_proposed Cloud Pak for Data | type=Data Engineering Tools subtype=Cloud Services nature=PLATFORM lifespan=MULTI_YEAR
canonical_skill_proposed DataStage | type=Data Engineering Tools subtype=ETL Tools nature=TOOL lifespan=MULTI_YEAR
dimension_skill_link_proposed Data Lake ↔ Cloud Storage and Data Services
dimension_skill_link_proposed Data Lake ↔ React Frontend Development
nano JD Parser — gpt-4.1-nano click to toggle
RoleApplication Developer
CompanyAccenture
Experience8-10 years
DomainIT Services & Consulting
Location Bengaluru, India
JD type pass
Show raw JSON
{
  "JD_type": "pass",
  "about_company": {
    "source_marker": {
      "first_5_words": "Accenture is a global professional",
      "last_5_words": "and shared success for our clients"
    },
    "text": "Accenture is a global professional services company with leading capabilities in digital, cloud and security. Combining unmatched experience and specialized skills across more than 40 industries, we offer Strategy and Consulting, Interactive, Technology and Operations services-all powered by the world\u0027s largest network of Advanced Technology and Intelligent Operations centers. Our 514,000 people deliver on the promise of technology and human ingenuity every day, serving clients in more than 120 countries. We embrace the power of change to create value and shared success for our clients, people, shareholders, partners and communities.",
    "word_count": 84
  },
  "certifications": [],
  "company_name": "Accenture",
  "ctc": null,
  "domain": {
    "primary": {
      "aliases": [
        "ITES",
        "BPO",
        "Tech Consulting"
      ],
      "domain": "IT Services \u0026 Consulting"
    },
    "secondary": null
  },
  "education": [
    {
      "level": "Bachelor\u0027s",
      "qualification": "BTECH/BE - Any Discipline",
      "raw": "B-tech or BE",
      "requirement": "required"
    }
  ],
  "experience": {
    "max": 10,
    "min": 8,
    "raw": "8-10 years"
  },
  "job_locations": [
    {
      "aliases": [
        "Bangalore"
      ],
      "city": "Bengaluru",
      "country": "India",
      "state": null,
      "work_mode": null
    }
  ],
  "role": "Application Developer",
  "role_aliases": [
    "App Developer",
    "Software Developer",
    "Application Engineer"
  ],
  "role_archetype": "Engineering",
  "roles_and_responsibilities": [
    {
      "bullet_count": 5,
      "heading": "Key Responsibilities",
      "heading_was_present": true,
      "source_marker": {
        "first_5_words": "1. Designing enterprise data architecture",
        "last_5_words": "and Solution Approach"
      },
      "text": "1. Designing enterprise data architecture and designing building solution for Data Lake Data Warehouse ETL solutions\n2. Model and design the application data structure storage and integration\n3. IBM InfoSphere Suite of products Designated Capability Expert and provide SME support\n4. Enterprise application performance calibration technical guidance to project team and suggest improvements best practices and recommendations to project team\n5. RFP proposal with ADM estimator and Solution Approach",
      "word_count": 56
    },
    {
      "bullet_count": 3,
      "heading": "Technical Experience",
      "heading_was_present": true,
      "source_marker": {
        "first_5_words": "1. Experience to deploy Cloud",
        "last_5_words": "real time stages"
      },
      "text": "1. Experience to deploy Cloud Pak for Data for clients across various platforms\n2. Experience Cloud Pak for Data services and able to do integration between different services\n3. Strong experience on lDataStage integration with cloud Hadoop ecosystem real time stages",
      "word_count": 42
    },
    {
      "bullet_count": 4,
      "heading": "Professional Attributes",
      "heading_was_present": true,
      "source_marker": {
        "first_5_words": "1. Good communication skills and",
        "last_5_words": "to changes quickly"
      },
      "text": "1. Good communication skills and interpersonal skills\n2. Should have prior experience of leading a team being cooperative, collaborative, empathetic with the team members\n3. Should have strong analytical abilities and creative problem solving skills\n4. Should have the ability to adapt to changes quickly",
      "word_count": 52
    }
  ],
  "urls": [
    {
      "type": "website",
      "url": "http://www.accenture.com"
    }
  ]
}
API 1 — extract-from-jd click to toggle
{
  "final_skills": [
    {
      "is_primary": true,
      "skill_name": "Data Lake"
    },
    {
      "is_primary": true,
      "skill_name": "Data Warehouse"
    },
    {
      "is_primary": true,
      "skill_name": "ETL"
    },
    {
      "is_primary": true,
      "skill_name": "IBM InfoSphere"
    },
    {
      "is_primary": true,
      "skill_name": "Cloud Pak for Data"
    },
    {
      "is_primary": true,
      "skill_name": "DataStage"
    },
    {
      "is_primary": true,
      "skill_name": "Hadoop"
    }
  ],
  "jd_role": {
    "display_name": "Application Developer",
    "rationale": null,
    "role_aliases": [
      "App Developer",
      "Software Developer",
      "Application Engineer"
    ],
    "role_archetype": "Engineering",
    "slug": ""
  },
  "nano_parsed": {
    "JD_type": "pass",
    "about_company": {
      "source_marker": {
        "first_5_words": "Accenture is a global professional",
        "last_5_words": "and shared success for our clients"
      },
      "text": "Accenture is a global professional services company with leading capabilities in digital, cloud and security. Combining unmatched experience and specialized skills across more than 40 industries, we offer Strategy and Consulting, Interactive, Technology and Operations services-all powered by the world\u0027s largest network of Advanced Technology and Intelligent Operations centers. Our 514,000 people deliver on the promise of technology and human ingenuity every day, serving clients in more than 120 countries. We embrace the power of change to create value and shared success for our clients, people, shareholders, partners and communities.",
      "word_count": 84
    },
    "certifications": [],
    "company_name": "Accenture",
    "ctc": null,
    "domain": {
      "primary": {
        "aliases": [
          "ITES",
          "BPO",
          "Tech Consulting"
        ],
        "domain": "IT Services \u0026 Consulting"
      },
      "secondary": null
    },
    "education": [
      {
        "level": "Bachelor\u0027s",
        "qualification": "BTECH/BE - Any Discipline",
        "raw": "B-tech or BE",
        "requirement": "required"
      }
    ],
    "experience": {
      "max": 10,
      "min": 8,
      "raw": "8-10 years"
    },
    "job_locations": [
      {
        "aliases": [
          "Bangalore"
        ],
        "city": "Bengaluru",
        "country": "India",
        "state": null,
        "work_mode": null
      }
    ],
    "role": "Application Developer",
    "role_aliases": [
      "App Developer",
      "Software Developer",
      "Application Engineer"
    ],
    "role_archetype": "Engineering",
    "roles_and_responsibilities": [
      {
        "bullet_count": 5,
        "heading": "Key Responsibilities",
        "heading_was_present": true,
        "source_marker": {
          "first_5_words": "1. Designing enterprise data architecture",
          "last_5_words": "and Solution Approach"
        },
        "text": "1. Designing enterprise data architecture and designing building solution for Data Lake Data Warehouse ETL solutions\n2. Model and design the application data structure storage and integration\n3. IBM InfoSphere Suite of products Designated Capability Expert and provide SME support\n4. Enterprise application performance calibration technical guidance to project team and suggest improvements best practices and recommendations to project team\n5. RFP proposal with ADM estimator and Solution Approach",
        "word_count": 56
      },
      {
        "bullet_count": 3,
        "heading": "Technical Experience",
        "heading_was_present": true,
        "source_marker": {
          "first_5_words": "1. Experience to deploy Cloud",
          "last_5_words": "real time stages"
        },
        "text": "1. Experience to deploy Cloud Pak for Data for clients across various platforms\n2. Experience Cloud Pak for Data services and able to do integration between different services\n3. Strong experience on lDataStage integration with cloud Hadoop ecosystem real time stages",
        "word_count": 42
      },
      {
        "bullet_count": 4,
        "heading": "Professional Attributes",
        "heading_was_present": true,
        "source_marker": {
          "first_5_words": "1. Good communication skills and",
          "last_5_words": "to changes quickly"
        },
        "text": "1. Good communication skills and interpersonal skills\n2. Should have prior experience of leading a team being cooperative, collaborative, empathetic with the team members\n3. Should have strong analytical abilities and creative problem solving skills\n4. Should have the ability to adapt to changes quickly",
        "word_count": 52
      }
    ],
    "urls": [
      {
        "type": "website",
        "url": "http://www.accenture.com"
      }
    ]
  },
  "rejected": false,
  "rejection_reason": null,
  "run_id": "5c740f5f-a54f-4fe5-944b-7eadd2c9ad6c",
  "stage3_signals": {
    "alias_found": true,
    "alias_match_roles": [
      {
        "display_name": "Backend Developer",
        "kra_matches": null,
        "matched_count": null,
        "matched_skills": null,
        "role_id": 1,
        "score": 1.0,
        "slug": "backend-engineer",
        "total_count": null
      }
    ],
    "kra_match_roles": [
      {
        "display_name": "Data Engineer",
        "kra_matches": [
          {
            "kra_text": "Designs dimensional models, star schemas, data vault structures, and curated data mart tables to support BI tools and self-service analytics consumption.",
            "sentence": "Designing enterprise data architecture and designing building solution for Data Lake Data Warehouse ETL solutions",
            "similarity": 0.6247
          },
          {
            "kra_text": "Develops batch and real-time streaming data pipelines using Apache Spark, Apache Kafka, Apache Flink, or Airflow for data movement and processing at scale.",
            "sentence": "Strong experience on lDataStage integration with cloud Hadoop ecosystem real time stages",
            "similarity": 0.5315
          },
          {
            "kra_text": "Designs dimensional models, star schemas, data vault structures, and curated data mart tables to support BI tools and self-service analytics consumption.",
            "sentence": "IBM InfoSphere Suite of products Designated Capability Expert and provide SME support",
            "similarity": 0.5174
          }
        ],
        "matched_count": null,
        "matched_skills": null,
        "role_id": 2,
        "score": 0.5579,
        "slug": "data-engineer",
        "total_count": null
      },
      {
        "display_name": "Scala Backend Developer",
        "kra_matches": [
          {
            "kra_text": "application data modeling",
            "sentence": "Model and design the application data structure storage and integration",
            "similarity": 0.646
          },
          {
            "kra_text": "performance and reliability tuning",
            "sentence": "Enterprise application performance calibration technical guidance to project team and suggest improvements best practices and recommendations to project team",
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          },
          {
            "kra_text": "application data modeling",
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          }
        ],
        "matched_count": null,
        "matched_skills": null,
        "role_id": 87,
        "score": 0.5556,
        "slug": "scala-backend-developer",
        "total_count": null
      },
      {
        "display_name": "Svelte Frontend Developer",
        "kra_matches": [
          {
            "kra_text": "backend data integration",
            "sentence": "Model and design the application data structure storage and integration",
            "similarity": 0.5529
          },
          {
            "kra_text": "performance tuning",
            "sentence": "Enterprise application performance calibration technical guidance to project team and suggest improvements best practices and recommendations to project team",
            "similarity": 0.5412
          },
          {
            "kra_text": "backend data integration",
            "sentence": "Experience Cloud Pak for Data services and able to do integration between different services",
            "similarity": 0.5381
          }
        ],
        "matched_count": null,
        "matched_skills": null,
        "role_id": 92,
        "score": 0.5441,
        "slug": "svelte-frontend-developer",
        "total_count": null
      },
      {
        "display_name": "Java Backend Developer",
        "kra_matches": [
          {
            "kra_text": "backend performance tuning",
            "sentence": "Enterprise application performance calibration technical guidance to project team and suggest improvements best practices and recommendations to project team",
            "similarity": 0.5555
          },
          {
            "kra_text": "persistence and data modeling",
            "sentence": "Model and design the application data structure storage and integration",
            "similarity": 0.5337
          },
          {
            "kra_text": "persistence and data modeling",
            "sentence": "Designing enterprise data architecture and designing building solution for Data Lake Data Warehouse ETL solutions",
            "similarity": 0.4755
          }
        ],
        "matched_count": null,
        "matched_skills": null,
        "role_id": 79,
        "score": 0.5215,
        "slug": "java-backend-developer",
        "total_count": null
      },
      {
        "display_name": "PHP Backend Developer",
        "kra_matches": [
          {
            "kra_text": "data access and persistence patterns",
            "sentence": "Model and design the application data structure storage and integration",
            "similarity": 0.573
          },
          {
            "kra_text": "performance and reliability tuning",
            "sentence": "Enterprise application performance calibration technical guidance to project team and suggest improvements best practices and recommendations to project team",
            "similarity": 0.5723
          },
          {
            "kra_text": "external system integration",
            "sentence": "Experience Cloud Pak for Data services and able to do integration between different services",
            "similarity": 0.4108
          }
        ],
        "matched_count": null,
        "matched_skills": null,
        "role_id": 86,
        "score": 0.5187,
        "slug": "php-backend-developer",
        "total_count": null
      }
    ],
    "skill_match_roles": [
      {
        "display_name": "Data Engineer",
        "kra_matches": null,
        "matched_count": 1,
        "matched_skills": [
          "Hadoop"
        ],
        "role_id": 2,
        "score": 0.1429,
        "slug": "data-engineer",
        "total_count": 7
      }
    ]
  },
  "stage4_decision": {
    "alias_collision_detected": false,
    "case": "A",
    "chosen_role": {
      "display_name": "Backend Developer",
      "kra_matches": null,
      "matched_count": null,
      "matched_skills": null,
      "role_id": 1,
      "score": 1.0,
      "slug": "backend-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 backend-engineer (1.0) \u2014 no other alias at this confidence; skill_top data-engineer 0.14 does not contradict",
    "sub_role": null
  },
  "stage5_updates": {
    "centroid_n_after": 1692,
    "centroid_updated": true,
    "collision_log_id": null,
    "new_kra_attached": {
      "best_kra_similarity": 0.0,
      "queue_id": 1836,
      "r_and_r_preview": "1. Designing enterprise data architecture and designing building solution for Data Lake Data Warehouse ETL solutions\n2. Model and design the application data structure storage and integration\n3. IBM I",
      "role_display_name": "Backend Developer",
      "role_slug": "backend-engineer",
      "status": "pending"
    },
    "new_skills_attached": [
      {
        "is_primary": true,
        "queue_id": 24084,
        "role_display_name": "Backend Developer",
        "role_slug": "backend-engineer",
        "skill_name": "Data Lake",
        "status": "pending"
      },
      {
        "is_primary": true,
        "queue_id": 24086,
        "role_display_name": "Backend Developer",
        "role_slug": "backend-engineer",
        "skill_name": "Data Warehouse",
        "status": "pending"
      },
      {
        "is_primary": true,
        "queue_id": 24087,
        "role_display_name": "Backend Developer",
        "role_slug": "backend-engineer",
        "skill_name": "ETL",
        "status": "pending"
      },
      {
        "is_primary": true,
        "queue_id": 24088,
        "role_display_name": "Backend Developer",
        "role_slug": "backend-engineer",
        "skill_name": "IBM InfoSphere",
        "status": "pending"
      },
      {
        "is_primary": true,
        "queue_id": 24089,
        "role_display_name": "Backend Developer",
        "role_slug": "backend-engineer",
        "skill_name": "Cloud Pak for Data",
        "status": "pending"
      },
      {
        "is_primary": true,
        "queue_id": 24090,
        "role_display_name": "Backend Developer",
        "role_slug": "backend-engineer",
        "skill_name": "DataStage",
        "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": "TODO: REMOVE AFTER TESTING \u2014 alias DB write disabled",
      "alias_persisted": false,
      "existing_alias_id": 2017,
      "existing_alias_text": "Data Lakes",
      "input_term": "Data Lake",
      "matched_canonical": {
        "category_id": 1,
        "display_name": "Data Lakes",
        "id": 1358,
        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "PATTERN",
        "slug": "data-lakes",
        "sub_category_id": 1025,
        "typical_lifespan": "EVERGREEN",
        "volatility": "STABLE"
      },
      "matched_via": "embedding_alias"
    },
    {
      "alias_persist_skipped_reason": "alias_text already exists for this canonical skill",
      "alias_persisted": false,
      "existing_alias_id": 2010,
      "existing_alias_text": "Hadoop",
      "input_term": "Hadoop",
      "matched_canonical": {
        "category_id": 5,
        "display_name": "Hadoop",
        "id": 1351,
        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "FRAMEWORK",
        "slug": "hadoop",
        "sub_category_id": 91,
        "typical_lifespan": "EVERGREEN",
        "volatility": "STABLE"
      },
      "matched_via": "alias"
    }
  ],
  "candidate_roles": [
    {
      "display_name": "Cloud Architect",
      "id": 9,
      "rationale": null,
      "role_archetype": null,
      "slug": "cloud-architect",
      "source": "db"
    },
    {
      "display_name": "Data Engineer",
      "id": 2,
      "rationale": null,
      "role_archetype": null,
      "slug": "data-engineer",
      "source": "db"
    }
  ],
  "chosen_role": {
    "display_name": "Backend Developer",
    "id": 1,
    "rationale": "Exact alias hit on backend-engineer (1.0) \u2014 no other alias at this confidence; skill_top data-engineer 0.14 does not contradict",
    "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"
  },
  "dimensions": [
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "Cloud Storage and Data Services",
        "id": 144,
        "rationale": "Cloud-native storage and managed data services used to place workloads, choose durability tiers, and define platform boundaries. This is a coherent cluster because architects evaluate storage fit, access patterns, and managed service tradeoffs.",
        "slug": "cloud-storage-and-data-services",
        "source": "db"
      },
      "input_skill": "Data Lake",
      "llm_role": null,
      "roles_from_db": [
        {
          "display_name": "Cloud Architect",
          "id": 9,
          "rationale": null,
          "role_archetype": null,
          "slug": "cloud-architect",
          "source": "db"
        }
      ]
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "React Frontend Development",
        "id": 96,
        "rationale": "Building interactive web user interfaces with React.js, including component composition, state management, hooks, and rendering patterns. React.js belongs here because it is a core library for client-side UI development in modern web applications.",
        "slug": "d_init_01",
        "source": "db"
      },
      "input_skill": "Data Lake",
      "llm_role": null,
      "roles_from_db": []
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "ETL and ELT Tooling",
        "id": 24,
        "rationale": "Packaged tools for extracting, loading, and transforming data across systems. This dimension covers connector-based ingestion, transformation frameworks, and managed integration products.",
        "slug": "etl-and-elt-tooling",
        "source": "db"
      },
      "input_skill": "Hadoop",
      "llm_role": null,
      "roles_from_db": [
        {
          "display_name": "Data Engineer",
          "id": 2,
          "rationale": null,
          "role_archetype": null,
          "slug": "data-engineer",
          "source": "db"
        }
      ]
    }
  ],
  "input_final_skills": [
    "Data Lake",
    "Data Warehouse",
    "ETL",
    "IBM InfoSphere",
    "Cloud Pak for Data",
    "DataStage",
    "Hadoop"
  ],
  "input_llm_skills": [
    "Data Lake",
    "Data Warehouse",
    "ETL",
    "IBM InfoSphere",
    "Cloud Pak for Data",
    "DataStage",
    "Hadoop"
  ],
  "new_aliases_persisted": 0,
  "run_id": "5c740f5f-a54f-4fe5-944b-7eadd2c9ad6c",
  "skills_detail": [
    {
      "aliases_in_db": [
        {
          "alias_text": "Data Lakes",
          "alias_type": "CANONICAL",
          "id": 2017,
          "is_primary": false,
          "match_strategy": "CASE_INSENSITIVE"
        }
      ],
      "canonical": {
        "category_id": 1,
        "display_name": "Data Lakes",
        "id": 1358,
        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "PATTERN",
        "slug": "data-lakes",
        "sub_category_id": 1025,
        "typical_lifespan": "EVERGREEN",
        "volatility": "STABLE"
      },
      "dimensions": [
        {
          "dimension": {
            "difficulty_hint": "well_known",
            "display_name": "Cloud Storage and Data Services",
            "id": 144,
            "rationale": "Cloud-native storage and managed data services used to place workloads, choose durability tiers, and define platform boundaries. This is a coherent cluster because architects evaluate storage fit, access patterns, and managed service tradeoffs.",
            "slug": "cloud-storage-and-data-services",
            "source": "db"
          },
          "input_skill": "Data Lake",
          "llm_role": null,
          "roles_from_db": [
            {
              "display_name": "Cloud Architect",
              "id": 9,
              "rationale": null,
              "role_archetype": null,
              "slug": "cloud-architect",
              "source": "db"
            }
          ]
        },
        {
          "dimension": {
            "difficulty_hint": "well_known",
            "display_name": "React Frontend Development",
            "id": 96,
            "rationale": "Building interactive web user interfaces with React.js, including component composition, state management, hooks, and rendering patterns. React.js belongs here because it is a core library for client-side UI development in modern web applications.",
            "slug": "d_init_01",
            "source": "db"
          },
          "input_skill": "Data Lake",
          "llm_role": null,
          "roles_from_db": []
        }
      ],
      "input_skill": "Data Lake",
      "matched_via": "embedding_alias",
      "new_alias_persisted": false,
      "new_alias_text": null,
      "new_skill_meta": null,
      "source_tag": "db",
      "was_in_llm_skills": true
    },
    {
      "aliases_in_db": [],
      "canonical": null,
      "dimensions": [],
      "input_skill": "Data Warehouse",
      "matched_via": null,
      "new_alias_persisted": false,
      "new_alias_text": null,
      "new_skill_meta": {
        "derived": {
          "category": "Data Engineering Tools",
          "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": "data-warehouse",
        "split_log": [],
        "typed": null,
        "warnings": []
      },
      "source_tag": "llm",
      "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": "CONCEPT",
          "sub_category": "general",
          "typical_lifespan": "MULTI_YEAR",
          "version_strategy": "UNVERSIONED",
          "volatility": "MEDIUM"
        },
        "enrichment": null,
        "keep_log": [],
        "locked_dimensions": [],
        "merge_log": [],
        "placed": null,
        "relationships": null,
        "skill_id": "etl",
        "split_log": [],
        "typed": null,
        "warnings": []
      },
      "source_tag": "llm",
      "was_in_llm_skills": true
    },
    {
      "aliases_in_db": [],
      "canonical": null,
      "dimensions": [],
      "input_skill": "IBM InfoSphere",
      "matched_via": null,
      "new_alias_persisted": false,
      "new_alias_text": null,
      "new_skill_meta": {
        "derived": {
          "category": "Data Engineering Tools",
          "skill_nature": "TOOL",
          "sub_category": "ETL Tools",
          "typical_lifespan": "MULTI_YEAR",
          "version_strategy": "UNVERSIONED",
          "volatility": "MEDIUM"
        },
        "enrichment": null,
        "keep_log": [],
        "locked_dimensions": [],
        "merge_log": [],
        "placed": null,
        "relationships": null,
        "skill_id": "ibm-infosphere",
        "split_log": [],
        "typed": null,
        "warnings": []
      },
      "source_tag": "llm",
      "was_in_llm_skills": true
    },
    {
      "aliases_in_db": [],
      "canonical": null,
      "dimensions": [],
      "input_skill": "Cloud Pak for Data",
      "matched_via": null,
      "new_alias_persisted": false,
      "new_alias_text": null,
      "new_skill_meta": {
        "derived": {
          "category": "Data Engineering Tools",
          "skill_nature": "PLATFORM",
          "sub_category": "Cloud Services",
          "typical_lifespan": "MULTI_YEAR",
          "version_strategy": "UNVERSIONED",
          "volatility": "MEDIUM"
        },
        "enrichment": null,
        "keep_log": [],
        "locked_dimensions": [],
        "merge_log": [],
        "placed": null,
        "relationships": null,
        "skill_id": "cloud-pak-for-data",
        "split_log": [],
        "typed": null,
        "warnings": []
      },
      "source_tag": "llm",
      "was_in_llm_skills": true
    },
    {
      "aliases_in_db": [],
      "canonical": null,
      "dimensions": [],
      "input_skill": "DataStage",
      "matched_via": null,
      "new_alias_persisted": false,
      "new_alias_text": null,
      "new_skill_meta": {
        "derived": {
          "category": "Data Engineering Tools",
          "skill_nature": "TOOL",
          "sub_category": "ETL Tools",
          "typical_lifespan": "MULTI_YEAR",
          "version_strategy": "UNVERSIONED",
          "volatility": "MEDIUM"
        },
        "enrichment": null,
        "keep_log": [],
        "locked_dimensions": [],
        "merge_log": [],
        "placed": null,
        "relationships": null,
        "skill_id": "datastage",
        "split_log": [],
        "typed": null,
        "warnings": []
      },
      "source_tag": "llm",
      "was_in_llm_skills": true
    },
    {
      "aliases_in_db": [
        {
          "alias_text": "Hadoop",
          "alias_type": "CANONICAL",
          "id": 2010,
          "is_primary": false,
          "match_strategy": "CASE_INSENSITIVE"
        }
      ],
      "canonical": {
        "category_id": 5,
        "display_name": "Hadoop",
        "id": 1351,
        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "FRAMEWORK",
        "slug": "hadoop",
        "sub_category_id": 91,
        "typical_lifespan": "EVERGREEN",
        "volatility": "STABLE"
      },
      "dimensions": [
        {
          "dimension": {
            "difficulty_hint": "well_known",
            "display_name": "ETL and ELT Tooling",
            "id": 24,
            "rationale": "Packaged tools for extracting, loading, and transforming data across systems. This dimension covers connector-based ingestion, transformation frameworks, and managed integration products.",
            "slug": "etl-and-elt-tooling",
            "source": "db"
          },
          "input_skill": "Hadoop",
          "llm_role": null,
          "roles_from_db": [
            {
              "display_name": "Data Engineer",
              "id": 2,
              "rationale": null,
              "role_archetype": null,
              "slug": "data-engineer",
              "source": "db"
            }
          ]
        }
      ],
      "input_skill": "Hadoop",
      "matched_via": "alias",
      "new_alias_persisted": false,
      "new_alias_text": null,
      "new_skill_meta": null,
      "source_tag": "db",
      "was_in_llm_skills": true
    }
  ],
  "unmatched_skills": [
    "Data Warehouse",
    "ETL",
    "IBM InfoSphere",
    "Cloud Pak for Data",
    "DataStage"
  ]
}
API 3 — final-role-output
{
  "chosen_role": {
    "display_name": "Backend Developer",
    "id": 1,
    "rationale": "Exact alias hit on backend-engineer (1.0) \u2014 no other alias at this confidence; skill_top data-engineer 0.14 does not contradict",
    "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"
  },
  "chosen_role_resolution": "in_db",
  "final_input_skills": [
    {
      "skill": "Data Lake",
      "tag": "in_db"
    },
    {
      "skill": "Data Warehouse",
      "tag": "new"
    },
    {
      "skill": "ETL",
      "tag": "new"
    },
    {
      "skill": "IBM InfoSphere",
      "tag": "new"
    },
    {
      "skill": "Cloud Pak for Data",
      "tag": "new"
    },
    {
      "skill": "DataStage",
      "tag": "new"
    },
    {
      "skill": "Hadoop",
      "tag": "in_db"
    }
  ],
  "llm_cost_api1_usd": null,
  "llm_cost_api2_usd": null,
  "llm_cost_api3_usd": null,
  "llm_cost_total_usd": null,
  "persistence": {
    "items": [
      {
        "chosen_role_id": 1,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Cloud Storage and Data Services",
          "id": 144,
          "rationale": "Cloud-native storage and managed data services used to place workloads, choose durability tiers, and define platform boundaries. This is a coherent cluster because architects evaluate storage fit, access patterns, and managed service tradeoffs.",
          "slug": "cloud-storage-and-data-services",
          "source": "db"
        },
        "dimension_id": 144,
        "input_skill": "Data Lake",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "Skipped \u2014 no persistable v3 meta for new skill",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": "Cloud Architect",
            "id": 9,
            "rationale": null,
            "role_archetype": null,
            "slug": "cloud-architect",
            "source": "db"
          }
        ],
        "skill_dimension_saved": false,
        "skill_id": null,
        "skill_tag": "new",
        "skipped_reason": "skill_not_in_db_v3_proposed"
      },
      {
        "chosen_role_id": 1,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "React Frontend Development",
          "id": 96,
          "rationale": "Building interactive web user interfaces with React.js, including component composition, state management, hooks, and rendering patterns. React.js belongs here because it is a core library for client-side UI development in modern web applications.",
          "slug": "d_init_01",
          "source": "db"
        },
        "dimension_id": 96,
        "input_skill": "Data Lake",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "Skipped \u2014 no persistable v3 meta for new skill",
        "role_dimension_saved": false,
        "roles_from_db": [],
        "skill_dimension_saved": false,
        "skill_id": null,
        "skill_tag": "new",
        "skipped_reason": "skill_not_in_db_v3_proposed"
      },
      {
        "chosen_role_id": 1,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "ETL and ELT Tooling",
          "id": 24,
          "rationale": "Packaged tools for extracting, loading, and transforming data across systems. This dimension covers connector-based ingestion, transformation frameworks, and managed integration products.",
          "slug": "etl-and-elt-tooling",
          "source": "db"
        },
        "dimension_id": 24,
        "input_skill": "Hadoop",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": "Data Engineer",
            "id": 2,
            "rationale": null,
            "role_archetype": null,
            "slug": "data-engineer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 1351,
        "skill_tag": "in_db",
        "skipped_reason": null
      }
    ],
    "new_skills_created": 0,
    "role_dimension_saved": 0,
    "skill_dimension_saved": 0,
    "skipped": 2
  },
  "planner_output": null,
  "run_id": "5c740f5f-a54f-4fe5-944b-7eadd2c9ad6c"
}