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Pipeline run

d54c7321-7ebe-4c10-ba9c-011f81a839fc

Pipeline LLM cost (USD)
API 1: $0.0067 API 2: $0.0001 API 3: $0.0000 Total: $0.0068

Client output enrichment

v2 Skill cluster · Nature of work · AI index · Tech stack maturity · Evidence · KRA description
SPARSE JD sources · ai_index: jd · nature_of_work: jd · tech_stack_maturity: jd
Nature of work · Data Integration / ETL
Build and support cloud data integration work in Informatica IICS and SQL, with Snowflake handling, while explaining technical solutions and design choices directly to business users/stakeholders.
"Expertise in SQL with related analytical skills."
Tech stack maturity
Modern Cloud Native
Snowflake and SQL for ETL/ELT are strongly associated with cloud-native data warehousing and modern data stack practices.
AI index (0 = no AI use, 5 = totally AI-dependent · v2.1)
0.20 / 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): AI, ML, AI/ML
Evidence — skills matched in JD (3)
Informatica Intelligent Cloud Services SQL Snowflake
Skill cluster (1 dimension groups, role-scoped)
Cross-cutting / unaligned
Informatica Intelligent Cloud Services SQL Snowflake
Show KRA description ↓
4 years of technical experience in Informatica Intelligent Cloud Services. (IICS) Expertise in SQL with related analytical skills. Good knowledge/ minimum 1 year experience in Cloud Data Warehouse- Snowflake Experience in demonstrating technical solutions to end-users. Excellent business communication skills (verbal and written in English) to articulate problems, make design decisions and to independently engage with business stakeholders throughout various phases of the project.

Signals

Skill data-engineer
0.67
Alias
KRA data-engineer
0.39

Post-classification

Centroidupdated · n=18
Alias collision log
New-role queue
New skills captured1
New KRA capturedyes

Captured for admin review

Informatica Intelligent Cloud Services primary ETL / ELT Developer pending
R&R fragment (sim 0.00) ETL / ELT Developer pending

4 years of technical experience in Informatica Intelligent Cloud Services. (IICS) Expertise in SQL with related analytical skills. Good knowledge/ minimum 1 year experience in Cloud Data Warehouse- Sn…

Status: completed Created: 2026-05-27T17:19:52.265142Z Updated: 2026-05-27T17:20:31.108866Z API 3 duration: 5157 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

ETL / ELT Developer

domain · Data Engineering & Analytics CASE DOMAIN

slug: etl-elt-developer · id: 50 · source: db

Domain=Data Engineering & Analytics; The JD centers on Informatica Intelligent Cloud Services, SQL, and cloud data warehouse work, which aligns best with ETL/ELT development.

Matched skills

Informatica Intelligent Cloud ServicesIICSSQLCloud Data WarehouseSnowflake

Matched dimensions

ETL/ELT DevelopmentCloud Data WarehousingTechnical Solution DemonstrationBusiness Stakeholder Communication

Matched KRAs

technical experience in Informatica Intelligent Cloud ServicesExpertise in SQL with related analytical skillsexperience in Cloud Data Warehouse- Snowflakedemonstrating technical solutions to end-usersengage with business stakeholders throughout various phases of the project

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

Job Description :- Bachelor's degree, preferably in Computer Science or related discipline or equivalent years of relevant experience.- 4 years of technical experience in Informatica Intelligent Cloud Services. (IICS)- Expertise in SQL with related analytical skills.- Good knowledge/ minimum 1 year experience in Cloud Data Warehouse- Snowflake- Experience in demonstrating technical solutions to end-users.- Excellent business communication skills (verbal and written in English) to articulate problems, make design decisions and to independently engage with business stakeholders throughout various phases of the project.Note: Looking for someone who can join immediately or within 20 days.About Company :Infometry Inc is a pure play Business intelligence company, located in Bay Area( Fremont, CA). Also, have offshore locations in Bangalore and Singapore. We are leading Data Analytics company, Certified Engineering, Implementation partner for Informatica, Tableau, Snowflake, Matillion, Talend, Google Cloud (GCP), Dell Boomi, Adaptive Insights, CallidusCloud. We help in BI Strategy, Cloud Data Integration, Big Data, AI/ML, Enterprise Reporting, Executive Dashboards, Vertical Solutions, Cloud Strategy, Cloud Data Warehouse migration, PowerCenter to Cloud migration, Snowflakes Migration, and optimizing the IICS infrastructure. It is both service and product based company. We have developed products likes Informatica Google connectors and Infofiscus based on Informatica Technology. We have developed more than 14+ Connectors for Informatica and currently owns IP for Google Sheets, Google Drive, Google PubSub, Google BigTable, Adaptive Insights, and Hubspot. (ref:hirist.com)

Skills from this JD

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

Informatica Intelligent Cloud Services 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 skipped (dimension not under chosen role)
Snowflake Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: Snowflake id=105 · snowflake

Aliases — catalog

  • Snowflake (CANONICAL) primary

Context tags (catalog)

ELT ETL SQL Snowpark Snowpipe Streams Tasks Time Travel VARIANT data sharing data warehouse dbt semi-structured data virtual warehouse zero-copy cloning

Stored enrichment (catalog DB)

Category
Platform
Sub-category
Data Cloud Platform
Vendor
Snowflake Inc.
License
proprietary
Year introduced
2012
Confidence
0.98
Version strategy
NOT_APPLICABLE

Maturity reasoning: Snowflake appears frequently in data/analytics job postings and is a standard cloud data warehouse platform alongside BigQuery and Redshift.

Skill profile (library / DB)

Skill nature
PLATFORM
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
9
Sub-category id
113
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 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
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 skipped (dimension not under chosen role)
Snowflake in_db
Cloud Data Warehouses
cloud-data-warehouses
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)

Library artifacts (this run)

Kind Detail DB id
canonical_skill_proposed Informatica Intelligent Cloud Services | type=Cloud Platforms subtype=general nature=PLATFORM lifespan=MULTI_YEAR
nano JD Parser — gpt-4.1-nano click to toggle
CompanyInfometry Inc
Experience4 years of technical experience in Informatica Intelligent Cloud Services.
DomainIT Services & Consulting
Location Fremont, United States
JD type pass
Show raw JSON
{
  "JD_type": "pass",
  "about_company": {
    "source_marker": {
      "first_5_words": "Infometry Inc is a pure",
      "last_5_words": "Google BigTable, Adaptive Insights, and Hubspot."
    },
    "text": "Infometry Inc is a pure play Business intelligence company, located in Bay Area( Fremont, CA). Also, have offshore locations in Bangalore and Singapore. We are leading Data Analytics company, Certified Engineering, Implementation partner for Informatica, Tableau, Snowflake, Matillion, Talend, Google Cloud (GCP), Dell Boomi, Adaptive Insights, CallidusCloud. We help in BI Strategy, Cloud Data Integration, Big Data, AI/ML, Enterprise Reporting, Executive Dashboards, Vertical Solutions, Cloud Strategy, Cloud Data Warehouse migration, PowerCenter to Cloud migration, Snowflakes Migration, and optimizing the IICS infrastructure. It is both service and product based company. We have developed products likes Informatica Google connectors and Infofiscus based on Informatica Technology. We have developed more than 14+ Connectors for Informatica and currently owns IP for Google Sheets, Google Drive, Google PubSub, Google BigTable, Adaptive Insights, and Hubspot.",
    "word_count": 164
  },
  "archetype_override_applied": true,
  "archetype_override_matched_skills": [
    "Snowflake",
    "Informatica",
    "Matillion",
    "Tableau",
    "dashboards",
    "GCP",
    "Make",
    "Analytics",
    "Cloud",
    "SQL"
  ],
  "certifications": [],
  "company_name": "Infometry Inc",
  "ctc": null,
  "domain": {
    "primary": {
      "aliases": [
        "Business Intelligence",
        "Data Analytics"
      ],
      "domain": "IT Services \u0026 Consulting"
    },
    "secondary": null
  },
  "education": [
    {
      "level": "Bachelor\u0027s",
      "qualification": "BTECH/BE/BSC - Computer Science (or related)",
      "raw": "Bachelor\u0027s degree, preferably in Computer Science or related discipline or equivalent years of relevant experience.",
      "requirement": "required"
    }
  ],
  "experience": {
    "max": null,
    "min": 4,
    "raw": "4 years of technical experience in Informatica Intelligent Cloud Services."
  },
  "job_locations": [
    {
      "aliases": [
        "Bay Area"
      ],
      "city": "Fremont",
      "country": "United States",
      "state": "California",
      "work_mode": null
    },
    {
      "aliases": [],
      "city": "Bangalore",
      "country": "India",
      "state": null,
      "work_mode": null
    },
    {
      "aliases": [],
      "city": "Singapore",
      "country": "Singapore",
      "state": null,
      "work_mode": null
    }
  ],
  "role": null,
  "role_aliases": [],
  "role_archetype": "Engineering",
  "roles_and_responsibilities": [
    {
      "bullet_count": 5,
      "heading": "Qualifications",
      "heading_was_present": true,
      "source_marker": {
        "first_5_words": "4 years of technical experience",
        "last_5_words": "various phases of the project."
      },
      "text": "4 years of technical experience in Informatica Intelligent Cloud Services. (IICS)\nExpertise in SQL with related analytical skills.\nGood knowledge/ minimum 1 year experience in Cloud Data Warehouse- Snowflake\nExperience in demonstrating technical solutions to end-users.\nExcellent business communication skills (verbal and written in English) to articulate problems, make design decisions and to independently engage with business stakeholders throughout various phases of the project.",
      "word_count": 56
    }
  ],
  "urls": []
}
API 1 — extract-from-jd click to toggle
{
  "final_skills": [
    {
      "is_primary": true,
      "skill_name": "Informatica Intelligent Cloud Services"
    },
    {
      "is_primary": true,
      "skill_name": "SQL"
    },
    {
      "is_primary": true,
      "skill_name": "Snowflake"
    }
  ],
  "jd_role": null,
  "nano_parsed": {
    "JD_type": "pass",
    "about_company": {
      "source_marker": {
        "first_5_words": "Infometry Inc is a pure",
        "last_5_words": "Google BigTable, Adaptive Insights, and Hubspot."
      },
      "text": "Infometry Inc is a pure play Business intelligence company, located in Bay Area( Fremont, CA). Also, have offshore locations in Bangalore and Singapore. We are leading Data Analytics company, Certified Engineering, Implementation partner for Informatica, Tableau, Snowflake, Matillion, Talend, Google Cloud (GCP), Dell Boomi, Adaptive Insights, CallidusCloud. We help in BI Strategy, Cloud Data Integration, Big Data, AI/ML, Enterprise Reporting, Executive Dashboards, Vertical Solutions, Cloud Strategy, Cloud Data Warehouse migration, PowerCenter to Cloud migration, Snowflakes Migration, and optimizing the IICS infrastructure. It is both service and product based company. We have developed products likes Informatica Google connectors and Infofiscus based on Informatica Technology. We have developed more than 14+ Connectors for Informatica and currently owns IP for Google Sheets, Google Drive, Google PubSub, Google BigTable, Adaptive Insights, and Hubspot.",
      "word_count": 164
    },
    "archetype_override_applied": true,
    "archetype_override_matched_skills": [
      "Snowflake",
      "Informatica",
      "Matillion",
      "Tableau",
      "dashboards",
      "GCP",
      "Make",
      "Analytics",
      "Cloud",
      "SQL"
    ],
    "certifications": [],
    "company_name": "Infometry Inc",
    "ctc": null,
    "domain": {
      "primary": {
        "aliases": [
          "Business Intelligence",
          "Data Analytics"
        ],
        "domain": "IT Services \u0026 Consulting"
      },
      "secondary": null
    },
    "education": [
      {
        "level": "Bachelor\u0027s",
        "qualification": "BTECH/BE/BSC - Computer Science (or related)",
        "raw": "Bachelor\u0027s degree, preferably in Computer Science or related discipline or equivalent years of relevant experience.",
        "requirement": "required"
      }
    ],
    "experience": {
      "max": null,
      "min": 4,
      "raw": "4 years of technical experience in Informatica Intelligent Cloud Services."
    },
    "job_locations": [
      {
        "aliases": [
          "Bay Area"
        ],
        "city": "Fremont",
        "country": "United States",
        "state": "California",
        "work_mode": null
      },
      {
        "aliases": [],
        "city": "Bangalore",
        "country": "India",
        "state": null,
        "work_mode": null
      },
      {
        "aliases": [],
        "city": "Singapore",
        "country": "Singapore",
        "state": null,
        "work_mode": null
      }
    ],
    "role": null,
    "role_aliases": [],
    "role_archetype": "Engineering",
    "roles_and_responsibilities": [
      {
        "bullet_count": 5,
        "heading": "Qualifications",
        "heading_was_present": true,
        "source_marker": {
          "first_5_words": "4 years of technical experience",
          "last_5_words": "various phases of the project."
        },
        "text": "4 years of technical experience in Informatica Intelligent Cloud Services. (IICS)\nExpertise in SQL with related analytical skills.\nGood knowledge/ minimum 1 year experience in Cloud Data Warehouse- Snowflake\nExperience in demonstrating technical solutions to end-users.\nExcellent business communication skills (verbal and written in English) to articulate problems, make design decisions and to independently engage with business stakeholders throughout various phases of the project.",
        "word_count": 56
      }
    ],
    "urls": []
  },
  "rejected": false,
  "rejection_reason": null,
  "run_id": "d54c7321-7ebe-4c10-ba9c-011f81a839fc",
  "stage3_signals": {
    "alias_found": false,
    "alias_match_roles": [],
    "kra_match_roles": [
      {
        "display_name": "Data Engineer",
        "kra_matches": [
          {
            "kra_text": "Optimizes pipeline throughput, partitioning strategies, and query performance across cloud data warehouses like Snowflake, BigQuery, or Redshift.",
            "sentence": "Good knowledge/ minimum 1 year experience in Cloud Data Warehouse- Snowflake",
            "similarity": 0.4957
          },
          {
            "kra_text": "Works with data analysts, data scientists, and business stakeholders to define data models, ingestion schedules, and data delivery requirements.",
            "sentence": "Excellent business communication skills (verbal and written in English) to articulate problems, make design decisions and to independently engage with business stakeholders throughout various phases of the project.",
            "similarity": 0.3603
          },
          {
            "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": "4 years of technical experience in Informatica Intelligent Cloud Services. (IICS)",
            "similarity": 0.3189
          }
        ],
        "matched_count": null,
        "matched_skills": null,
        "role_id": 2,
        "score": 0.3916,
        "slug": "data-engineer",
        "total_count": null
      },
      {
        "display_name": "Cloud Architect",
        "kra_matches": [
          {
            "kra_text": "Conducts architecture reviews, approves technical design documents, and guides engineering teams through cloud migration and modernization projects.",
            "sentence": "Excellent business communication skills (verbal and written in English) to articulate problems, make design decisions and to independently engage with business stakeholders throughout various phases of the project.",
            "similarity": 0.409
          },
          {
            "kra_text": "Designs IAM policies, service control policies, VPC segmentation, private endpoints, and zero-trust network access boundaries for cloud environments.",
            "sentence": "4 years of technical experience in Informatica Intelligent Cloud Services. (IICS)",
            "similarity": 0.376
          },
          {
            "kra_text": "Establishes cloud environment standards including VPC topology, workload placement policies, resource tagging taxonomies, and account structure.",
            "sentence": "Good knowledge/ minimum 1 year experience in Cloud Data Warehouse- Snowflake",
            "similarity": 0.337
          }
        ],
        "matched_count": null,
        "matched_skills": null,
        "role_id": 9,
        "score": 0.374,
        "slug": "cloud-architect",
        "total_count": null
      },
      {
        "display_name": "Cloud Security Engineer",
        "kra_matches": [
          {
            "kra_text": "Reviews cloud infrastructure-as-code configurations for security misconfigurations and implements CIS Benchmark hardening baselines using CSPM tools.",
            "sentence": "4 years of technical experience in Informatica Intelligent Cloud Services. (IICS)",
            "similarity": 0.3725
          },
          {
            "kra_text": "Configures cloud data protection including column-level encryption, DLP scanning policies, and data classification labels for regulated data.",
            "sentence": "Good knowledge/ minimum 1 year experience in Cloud Data Warehouse- Snowflake",
            "similarity": 0.3626
          },
          {
            "kra_text": "Documents cloud security standards, approved architecture patterns, security exceptions, and remediation guidance for engineering teams.",
            "sentence": "Excellent business communication skills (verbal and written in English) to articulate problems, make design decisions and to independently engage with business stakeholders throughout various phases of the project.",
            "similarity": 0.3315
          }
        ],
        "matched_count": null,
        "matched_skills": null,
        "role_id": 23,
        "score": 0.3555,
        "slug": "cloud-security-engineer",
        "total_count": null
      },
      {
        "display_name": "Engineering Manager",
        "kra_matches": [
          {
            "kra_text": "facilitate technical and delivery decisions",
            "sentence": "Excellent business communication skills (verbal and written in English) to articulate problems, make design decisions and to independently engage with business stakeholders throughout various phases of the project.",
            "similarity": 0.4268
          },
          {
            "kra_text": "facilitate technical and delivery decisions",
            "sentence": "4 years of technical experience in Informatica Intelligent Cloud Services. (IICS)",
            "similarity": 0.3434
          },
          {
            "kra_text": "facilitate technical and delivery decisions",
            "sentence": "Good knowledge/ minimum 1 year experience in Cloud Data Warehouse- Snowflake",
            "similarity": 0.2899
          }
        ],
        "matched_count": null,
        "matched_skills": null,
        "role_id": 121,
        "score": 0.3533,
        "slug": "engineering-manager",
        "total_count": null
      },
      {
        "display_name": "Fullstack Developer",
        "kra_matches": [
          {
            "kra_text": "Works closely with product managers and UX designers to translate requirements and wireframes into working software features through iterative development.",
            "sentence": "Excellent business communication skills (verbal and written in English) to articulate problems, make design decisions and to independently engage with business stakeholders throughout various phases of the project.",
            "similarity": 0.4361
          },
          {
            "kra_text": "Designs and queries relational databases like PostgreSQL and document stores like MongoDB, writing migrations, indexes, and optimized queries.",
            "sentence": "Good knowledge/ minimum 1 year experience in Cloud Data Warehouse- Snowflake",
            "similarity": 0.3365
          },
          {
            "kra_text": "Delivers features through CI/CD pipelines using automated tests, staged rollouts, feature flags, and incremental deployments.",
            "sentence": "4 years of technical experience in Informatica Intelligent Cloud Services. (IICS)",
            "similarity": 0.2455
          }
        ],
        "matched_count": null,
        "matched_skills": null,
        "role_id": 15,
        "score": 0.3394,
        "slug": "full-stack-engineer",
        "total_count": null
      }
    ],
    "skill_match_roles": [
      {
        "display_name": "Data Engineer",
        "kra_matches": null,
        "matched_count": 2,
        "matched_skills": [
          "SQL",
          "Snowflake"
        ],
        "role_id": 2,
        "score": 0.6667,
        "slug": "data-engineer",
        "total_count": 3
      },
      {
        "display_name": "Pega Developer",
        "kra_matches": null,
        "matched_count": 1,
        "matched_skills": [
          "SQL"
        ],
        "role_id": 24,
        "score": 0.3333,
        "slug": "pega-developer",
        "total_count": 3
      },
      {
        "display_name": "Engineering Manager",
        "kra_matches": null,
        "matched_count": 1,
        "matched_skills": [
          "SQL"
        ],
        "role_id": 121,
        "score": 0.3333,
        "slug": "engineering-manager",
        "total_count": 3
      }
    ]
  },
  "stage4_decision": {
    "alias_collision_detected": false,
    "case": "DOMAIN",
    "chosen_role": {
      "display_name": "ETL / ELT Developer",
      "kra_matches": null,
      "matched_count": null,
      "matched_skills": null,
      "role_id": 50,
      "score": 0.96,
      "slug": "etl-elt-developer",
      "total_count": null
    },
    "confidence": 0.96,
    "is_new_role": false,
    "llm2_fired": false,
    "llm2_reasoning": null,
    "matched_dimensions": [
      "ETL/ELT Development",
      "Cloud Data Warehousing",
      "Technical Solution Demonstration",
      "Business Stakeholder Communication"
    ],
    "matched_kras": [
      "technical experience in Informatica Intelligent Cloud Services",
      "Expertise in SQL with related analytical skills",
      "experience in Cloud Data Warehouse- Snowflake",
      "demonstrating technical solutions to end-users",
      "engage with business stakeholders throughout various phases of the project"
    ],
    "matched_skills": [
      "Informatica Intelligent Cloud Services",
      "IICS",
      "SQL",
      "Cloud Data Warehouse",
      "Snowflake"
    ],
    "new_role_display_name": null,
    "new_role_slug": null,
    "queued": false,
    "reasoning": "Domain=Data Engineering \u0026 Analytics; The JD centers on Informatica Intelligent Cloud Services, SQL, and cloud data warehouse work, which aligns best with ETL/ELT development.",
    "sub_role": null
  },
  "stage5_updates": {
    "centroid_n_after": 18,
    "centroid_updated": true,
    "collision_log_id": null,
    "new_kra_attached": {
      "best_kra_similarity": 0.0,
      "queue_id": 1786,
      "r_and_r_preview": "4 years of technical experience in Informatica Intelligent Cloud Services. (IICS)\nExpertise in SQL with related analytical skills.\nGood knowledge/ minimum 1 year experience in Cloud Data Warehouse- Sn",
      "role_display_name": "ETL / ELT Developer",
      "role_slug": "etl-elt-developer",
      "status": "pending"
    },
    "new_skills_attached": [
      {
        "is_primary": true,
        "queue_id": 23503,
        "role_display_name": "ETL / ELT Developer",
        "role_slug": "etl-elt-developer",
        "skill_name": "Informatica Intelligent Cloud Services",
        "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": 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": 299,
      "existing_alias_text": "Snowflake",
      "input_term": "Snowflake",
      "matched_canonical": {
        "category_id": 9,
        "display_name": "Snowflake",
        "id": 105,
        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "PLATFORM",
        "slug": "snowflake",
        "sub_category_id": 113,
        "typical_lifespan": "EVERGREEN",
        "volatility": "STABLE"
      },
      "matched_via": "alias"
    }
  ],
  "candidate_roles": [
    {
      "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": "Data Engineer",
      "id": 2,
      "rationale": null,
      "role_archetype": null,
      "slug": "data-engineer",
      "source": "db"
    }
  ],
  "chosen_role": {
    "display_name": "ETL / ELT Developer",
    "id": 50,
    "rationale": "Domain=Data Engineering \u0026 Analytics; The JD centers on Informatica Intelligent Cloud Services, SQL, and cloud data warehouse work, which aligns best with ETL/ELT development.",
    "role_archetype": "Data",
    "slug": "etl-elt-developer",
    "source": "db"
  },
  "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"
        }
      ]
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "Cloud Data Warehouses",
        "id": 22,
        "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.",
        "slug": "cloud-data-warehouses",
        "source": "db"
      },
      "input_skill": "Snowflake",
      "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": [
    "Informatica Intelligent Cloud Services",
    "SQL",
    "Snowflake"
  ],
  "input_llm_skills": [
    "Informatica Intelligent Cloud Services",
    "SQL",
    "Snowflake"
  ],
  "new_aliases_persisted": 0,
  "run_id": "d54c7321-7ebe-4c10-ba9c-011f81a839fc",
  "skills_detail": [
    {
      "aliases_in_db": [],
      "canonical": null,
      "dimensions": [],
      "input_skill": "Informatica Intelligent Cloud Services",
      "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": "informatica-intelligent-cloud-services",
        "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": [
        {
          "alias_text": "Snowflake",
          "alias_type": "CANONICAL",
          "id": 299,
          "is_primary": true,
          "match_strategy": "CASE_INSENSITIVE"
        }
      ],
      "canonical": {
        "category_id": 9,
        "display_name": "Snowflake",
        "id": 105,
        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "PLATFORM",
        "slug": "snowflake",
        "sub_category_id": 113,
        "typical_lifespan": "EVERGREEN",
        "volatility": "STABLE"
      },
      "dimensions": [
        {
          "dimension": {
            "difficulty_hint": "well_known",
            "display_name": "Cloud Data Warehouses",
            "id": 22,
            "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.",
            "slug": "cloud-data-warehouses",
            "source": "db"
          },
          "input_skill": "Snowflake",
          "llm_role": null,
          "roles_from_db": [
            {
              "display_name": "Data Engineer",
              "id": 2,
              "rationale": null,
              "role_archetype": null,
              "slug": "data-engineer",
              "source": "db"
            }
          ]
        }
      ],
      "input_skill": "Snowflake",
      "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": [
    "Informatica Intelligent Cloud Services"
  ]
}
API 3 — final-role-output
{
  "chosen_role": {
    "display_name": "ETL / ELT Developer",
    "id": 50,
    "rationale": "Domain=Data Engineering \u0026 Analytics; The JD centers on Informatica Intelligent Cloud Services, SQL, and cloud data warehouse work, which aligns best with ETL/ELT development.",
    "role_archetype": "Data",
    "slug": "etl-elt-developer",
    "source": "db"
  },
  "chosen_role_resolution": "in_db",
  "final_input_skills": [
    {
      "skill": "Informatica Intelligent Cloud Services",
      "tag": "new"
    },
    {
      "skill": "SQL",
      "tag": "in_db"
    },
    {
      "skill": "Snowflake",
      "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": 50,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Pega Programming Languages \u0026 DSLs",
          "id": 267,
          "rationale": "Programming languages and domain-specific languages used in Pega development.",
          "slug": "pega-programming-languages-dsls",
          "source": "db"
        },
        "dimension_id": 267,
        "input_skill": "SQL",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": "Pega Developer",
            "id": 24,
            "rationale": null,
            "role_archetype": null,
            "slug": "pega-developer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 101,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 50,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Programming Languages \u0026 DSLs",
          "id": 475,
          "rationale": "Oversee and guide the selection and effective use of programming and domain\u2010specific languages in software projects.",
          "slug": "programming-languages-dsls",
          "source": "db"
        },
        "dimension_id": 475,
        "input_skill": "SQL",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": "Engineering Manager",
            "id": 121,
            "rationale": null,
            "role_archetype": null,
            "slug": "engineering-manager",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 101,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 50,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Programming Languages for Data Work",
          "id": 21,
          "rationale": "Languages used to implement data pipelines, transformations, and operational glue. This is the primary coding surface for building ingestion, enrichment, and automation logic in data engineering.",
          "slug": "programming-languages-for-data-work",
          "source": "db"
        },
        "dimension_id": 21,
        "input_skill": "SQL",
        "llm_role": null,
        "matched_chosen_role": 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": 101,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 50,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Cloud Data Warehouses",
          "id": 22,
          "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.",
          "slug": "cloud-data-warehouses",
          "source": "db"
        },
        "dimension_id": 22,
        "input_skill": "Snowflake",
        "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": 105,
        "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": "d54c7321-7ebe-4c10-ba9c-011f81a839fc"
}