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Pipeline run

91f45d18-4cf4-4afd-9ee0-13dea7a04a85

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

Client output enrichment

v2 Skill cluster · Nature of work · AI index · Tech stack maturity · Evidence · KRA description
Nature of work
no_db_connection
Tech stack maturity
Mainstream Modern
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 (22)
Google Cloud Platform PySpark Spark Scala Hadoop HDFS Python Java Hive Cassandra Pig MySQL NoSQL Bash UNIX ETL Data Pipelines Data Modeling Data Marts GCP Data Tools Data Science DevOps
Skill cluster (0 dimension groups, role-scoped)
No dimension groups computed for this JD.
Show KRA description ↓
● Designing and developing complex and large-scale data structures and pipelines to organize, collect, and standardize data to generate insights and address reporting needs ● Writing complex ETL (Extract / Transform / Load) processes, designs database systems and develops tools for real-time and offline analytic processing ● Developing frameworks, standards & reference material for architecture and associated products ● Designing data marts and data models to support Data Science and other internal customers. ● Behaving as mentor to junior team members to provide technical advice ● Applying knowledge of gcp-data tools and products to consult and advise on additional efforts across multiple domains spanning broader enterprise ● Collaborating with data science team to transform data and integrate algorithms and models into highly available, production systems ● Using in-depth knowledge on Hadoop architecture and HDFS commands and experience designing & optimizing queries to build scalable, modular, and efficient data pipelines ● Using advanced programming skills in Python, Java, PySpark, or any of the major languages to build robust data pipelines and dynamic systems ● Integrating data from a variety of sources, assuring that they adhere to data quality and accessibility standards ● Experimenting with available tools and advice on new tools in order to determine optimal solution given the requirements dictated by the model/use case ● 5+ years Data Engineering experience ● 5+ years PySpark (Spark/Scala) ● 3+ years advanced knowledge in Hadoop architecture, HDFS commands and experience designing & optimising queries against data in the HDFS environment ● 2+ years' experience with Google Cloud Platform ( GCP ) ● Experience with bash shell scripts, UNIX utilities & UNIX Commands ● Experience building and implementing data transformation and processing solutions ● Advanced knowledge in Java, Python, Hive, Cassandra, Pig, MySQL or NoSQL or similar ● If you are passionate about DevOps and GCP, and if you thrive in a collaborative and fast-paced environment ● You like to solve puzzles and figure things out, how they work, how they operate etc. ● You thrive in an environment that constantly demands you to learn.

Signals

Skill backend-engineer
0.18
Alias data-engineer
0.67
KRA devops-engineer
0.39

Post-classification

Centroid
Alias collision log
New-role queue#34
New skills captured0
New KRA captured
Status: extract_from_jd_done Created: 2026-05-19T00:11:54.056775Z Updated: 2026-05-19T00:11:54.579666Z
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

No chosen role stored for this run.

Job description

Sr. GCP Data Engineer

Job Description-------------------------------------------




Work Mode: WFO
Start Date: Immediate
Description
We are looking for a Senior GCP Data Engineer who's confident, curious, and straightforward, a
great fit for our empowering and driven culture. The candidate’s determination and clear
communication will make our cloud-based solutions sharp and easy to understand. Candidates
need to solve problems effortlessly and effectively in the cloud. Join us if you're excited to be
part of a team that values clarity, confidence, and getting things done through cloud technology.
Responsibilities:
● Designing and developing complex and large-scale data structures and pipelines to
organize, collect, and standardize data to generate insights and address reporting needs
● Writing complex ETL (Extract / Transform / Load) processes, designs database systems
and develops tools for real-time and offline analytic processing
● Developing frameworks, standards & reference material for architecture and associated
products
● Designing data marts and data models to support Data Science and other internal
customers.
● Behaving as mentor to junior team members to provide technical advice
● Applying knowledge of gcp-data tools and products to consult and advise on additional
efforts across multiple domains spanning broader enterprise
● Collaborating with data science team to transform data and integrate algorithms and
models into highly available, production systems
● Using in-depth knowledge on Hadoop architecture and HDFS commands and experience
designing & optimizing queries to build scalable, modular, and efficient data pipelines
● Using advanced programming skills in Python, Java, PySpark, or any of the major
languages to build robust data pipelines and dynamic systems
● Integrating data from a variety of sources, assuring that they adhere to data quality and
accessibility standards
● Experimenting with available tools and advice on new tools in order to determine optimal
solution given the requirements dictated by the model/use case
Requirements:
● 5+ years Data Engineering experience
● 5+ years PySpark (Spark/Scala)
● 3+ years advanced knowledge in Hadoop architecture, HDFS commands and experience
designing & optimising queries against data in the HDFS environment
● 2+ years' experience with Google Cloud Platform ( GCP )
● Experience with bash shell scripts, UNIX utilities & UNIX Commands
● Experience building and implementing data transformation and processing solutions
● Advanced knowledge in Java, Python, Hive, Cassandra, Pig, MySQL or NoSQL or
similar
● If you are passionate about DevOps and GCP, and if you thrive in a collaborative and
fast-paced environment
● You like to solve puzzles and figure things out, how they work, how they operate etc.
● You thrive in an environment that constantly demands you to learn.

Skills from this JD

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

Google Cloud Platform Primary No API 2 row (run stopped after API 1 or history missing)
PySpark Primary No API 2 row (run stopped after API 1 or history missing)
Spark Primary No API 2 row (run stopped after API 1 or history missing)
Scala Primary No API 2 row (run stopped after API 1 or history missing)
Hadoop Primary No API 2 row (run stopped after API 1 or history missing)
HDFS Primary No API 2 row (run stopped after API 1 or history missing)
Python Primary No API 2 row (run stopped after API 1 or history missing)
Java Primary No API 2 row (run stopped after API 1 or history missing)
Hive Primary No API 2 row (run stopped after API 1 or history missing)
Cassandra Primary No API 2 row (run stopped after API 1 or history missing)
Pig Primary No API 2 row (run stopped after API 1 or history missing)
MySQL Primary No API 2 row (run stopped after API 1 or history missing)
NoSQL Primary No API 2 row (run stopped after API 1 or history missing)
Bash Primary No API 2 row (run stopped after API 1 or history missing)
UNIX Primary No API 2 row (run stopped after API 1 or history missing)
GCP Data Tools Secondary No API 2 row (run stopped after API 1 or history missing)
ETL Primary No API 2 row (run stopped after API 1 or history missing)
Data Pipelines Primary No API 2 row (run stopped after API 1 or history missing)
Data Modeling Primary No API 2 row (run stopped after API 1 or history missing)
Data Marts Primary No API 2 row (run stopped after API 1 or history missing)
Data Science Secondary No API 2 row (run stopped after API 1 or history missing)
DevOps Secondary No API 2 row (run stopped after API 1 or history missing)

Library artifacts (this run)

No artifact rows for this run.
nano JD Parser — gpt-4.1-nano click to toggle
RoleSr. GCP Data Engineer
Experience5+ years Data Engineering experience
DomainOther
JD type pass
Show raw JSON
{
  "JD_type": "pass",
  "about_company": null,
  "certifications": [],
  "company_name": null,
  "ctc": null,
  "domain": {
    "primary": {
      "aliases": [],
      "domain": "Other"
    },
    "secondary": null
  },
  "education": [],
  "experience": {
    "max": null,
    "min": 5,
    "raw": "5+ years Data Engineering experience"
  },
  "job_locations": [],
  "role": "Sr. GCP Data Engineer",
  "role_archetype": "Data",
  "roles_and_responsibilities": [
    {
      "bullet_count": 10,
      "heading": "Responsibilities",
      "heading_was_present": true,
      "source_marker": {
        "first_5_words": "Responsibilities: \u25cf Designing and developing",
        "last_5_words": "requirements dictated by the model/use case"
      },
      "text": "\u25cf Designing and developing complex and large-scale data structures and pipelines to organize, collect, and standardize data to generate insights and address reporting needs\n\u25cf Writing complex ETL (Extract / Transform / Load) processes, designs database systems and develops tools for real-time and offline analytic processing\n\u25cf Developing frameworks, standards \u0026 reference material for architecture and associated products\n\u25cf Designing data marts and data models to support Data Science and other internal customers.\n\u25cf Behaving as mentor to junior team members to provide technical advice\n\u25cf Applying knowledge of gcp-data tools and products to consult and advise on additional efforts across multiple domains spanning broader enterprise\n\u25cf Collaborating with data science team to transform data and integrate algorithms and models into highly available, production systems\n\u25cf Using in-depth knowledge on Hadoop architecture and HDFS commands and experience designing \u0026 optimizing queries to build scalable, modular, and efficient data pipelines\n\u25cf Using advanced programming skills in Python, Java, PySpark, or any of the major languages to build robust data pipelines and dynamic systems\n\u25cf Integrating data from a variety of sources, assuring that they adhere to data quality and accessibility standards\n\u25cf Experimenting with available tools and advice on new tools in order to determine optimal solution given the requirements dictated by the model/use case",
      "word_count": 218
    },
    {
      "bullet_count": 10,
      "heading": "Requirements",
      "heading_was_present": true,
      "source_marker": {
        "first_5_words": "Requirements: \u25cf 5+ years Data",
        "last_5_words": "demands you to learn."
      },
      "text": "\u25cf 5+ years Data Engineering experience\n\u25cf 5+ years PySpark (Spark/Scala)\n\u25cf 3+ years advanced knowledge in Hadoop architecture, HDFS commands and experience designing \u0026 optimising queries against data in the HDFS environment\n\u25cf 2+ years\u0027 experience with Google Cloud Platform ( GCP )\n\u25cf Experience with bash shell scripts, UNIX utilities \u0026 UNIX Commands\n\u25cf Experience building and implementing data transformation and processing solutions\n\u25cf Advanced knowledge in Java, Python, Hive, Cassandra, Pig, MySQL or NoSQL or similar\n\u25cf If you are passionate about DevOps and GCP, and if you thrive in a collaborative and fast-paced environment\n\u25cf You like to solve puzzles and figure things out, how they work, how they operate etc.\n\u25cf You thrive in an environment that constantly demands you to learn.",
      "word_count": 134
    }
  ],
  "urls": []
}
API 1 — extract-from-jd click to toggle
{
  "final_skills": [
    {
      "is_primary": true,
      "skill_name": "Google Cloud Platform"
    },
    {
      "is_primary": true,
      "skill_name": "PySpark"
    },
    {
      "is_primary": true,
      "skill_name": "Spark"
    },
    {
      "is_primary": true,
      "skill_name": "Scala"
    },
    {
      "is_primary": true,
      "skill_name": "Hadoop"
    },
    {
      "is_primary": true,
      "skill_name": "HDFS"
    },
    {
      "is_primary": true,
      "skill_name": "Python"
    },
    {
      "is_primary": true,
      "skill_name": "Java"
    },
    {
      "is_primary": true,
      "skill_name": "Hive"
    },
    {
      "is_primary": true,
      "skill_name": "Cassandra"
    },
    {
      "is_primary": true,
      "skill_name": "Pig"
    },
    {
      "is_primary": true,
      "skill_name": "MySQL"
    },
    {
      "is_primary": true,
      "skill_name": "NoSQL"
    },
    {
      "is_primary": true,
      "skill_name": "Bash"
    },
    {
      "is_primary": true,
      "skill_name": "UNIX"
    },
    {
      "is_primary": false,
      "skill_name": "GCP Data Tools"
    },
    {
      "is_primary": true,
      "skill_name": "ETL"
    },
    {
      "is_primary": true,
      "skill_name": "Data Pipelines"
    },
    {
      "is_primary": true,
      "skill_name": "Data Modeling"
    },
    {
      "is_primary": true,
      "skill_name": "Data Marts"
    },
    {
      "is_primary": false,
      "skill_name": "Data Science"
    },
    {
      "is_primary": false,
      "skill_name": "DevOps"
    }
  ],
  "jd_role": {
    "display_name": "Sr. GCP Data Engineer",
    "rationale": null,
    "role_archetype": "Data",
    "slug": ""
  },
  "nano_parsed": {
    "JD_type": "pass",
    "about_company": null,
    "certifications": [],
    "company_name": null,
    "ctc": null,
    "domain": {
      "primary": {
        "aliases": [],
        "domain": "Other"
      },
      "secondary": null
    },
    "education": [],
    "experience": {
      "max": null,
      "min": 5,
      "raw": "5+ years Data Engineering experience"
    },
    "job_locations": [],
    "role": "Sr. GCP Data Engineer",
    "role_archetype": "Data",
    "roles_and_responsibilities": [
      {
        "bullet_count": 10,
        "heading": "Responsibilities",
        "heading_was_present": true,
        "source_marker": {
          "first_5_words": "Responsibilities: \u25cf Designing and developing",
          "last_5_words": "requirements dictated by the model/use case"
        },
        "text": "\u25cf Designing and developing complex and large-scale data structures and pipelines to organize, collect, and standardize data to generate insights and address reporting needs\n\u25cf Writing complex ETL (Extract / Transform / Load) processes, designs database systems and develops tools for real-time and offline analytic processing\n\u25cf Developing frameworks, standards \u0026 reference material for architecture and associated products\n\u25cf Designing data marts and data models to support Data Science and other internal customers.\n\u25cf Behaving as mentor to junior team members to provide technical advice\n\u25cf Applying knowledge of gcp-data tools and products to consult and advise on additional efforts across multiple domains spanning broader enterprise\n\u25cf Collaborating with data science team to transform data and integrate algorithms and models into highly available, production systems\n\u25cf Using in-depth knowledge on Hadoop architecture and HDFS commands and experience designing \u0026 optimizing queries to build scalable, modular, and efficient data pipelines\n\u25cf Using advanced programming skills in Python, Java, PySpark, or any of the major languages to build robust data pipelines and dynamic systems\n\u25cf Integrating data from a variety of sources, assuring that they adhere to data quality and accessibility standards\n\u25cf Experimenting with available tools and advice on new tools in order to determine optimal solution given the requirements dictated by the model/use case",
        "word_count": 218
      },
      {
        "bullet_count": 10,
        "heading": "Requirements",
        "heading_was_present": true,
        "source_marker": {
          "first_5_words": "Requirements: \u25cf 5+ years Data",
          "last_5_words": "demands you to learn."
        },
        "text": "\u25cf 5+ years Data Engineering experience\n\u25cf 5+ years PySpark (Spark/Scala)\n\u25cf 3+ years advanced knowledge in Hadoop architecture, HDFS commands and experience designing \u0026 optimising queries against data in the HDFS environment\n\u25cf 2+ years\u0027 experience with Google Cloud Platform ( GCP )\n\u25cf Experience with bash shell scripts, UNIX utilities \u0026 UNIX Commands\n\u25cf Experience building and implementing data transformation and processing solutions\n\u25cf Advanced knowledge in Java, Python, Hive, Cassandra, Pig, MySQL or NoSQL or similar\n\u25cf If you are passionate about DevOps and GCP, and if you thrive in a collaborative and fast-paced environment\n\u25cf You like to solve puzzles and figure things out, how they work, how they operate etc.\n\u25cf You thrive in an environment that constantly demands you to learn.",
        "word_count": 134
      }
    ],
    "urls": []
  },
  "rejected": false,
  "rejection_reason": null,
  "run_id": "91f45d18-4cf4-4afd-9ee0-13dea7a04a85",
  "stage3_signals": {
    "alias_match_roles": [
      {
        "display_name": "Data Engineer",
        "matched_count": null,
        "role_id": 2,
        "score": 0.6667,
        "slug": "data-engineer",
        "total_count": null
      },
      {
        "display_name": "AI Engineer",
        "matched_count": null,
        "role_id": 13,
        "score": 0.3846,
        "slug": "ai-engineer",
        "total_count": null
      },
      {
        "display_name": "Frontend Engineer",
        "matched_count": null,
        "role_id": 7,
        "score": 0.375,
        "slug": "frontend-engineer",
        "total_count": null
      },
      {
        "display_name": "ML Engineer",
        "matched_count": null,
        "role_id": 3,
        "score": 0.375,
        "slug": "ml-engineer",
        "total_count": null
      },
      {
        "display_name": "AR/VR Engineer",
        "matched_count": null,
        "role_id": 8,
        "score": 0.375,
        "slug": "ar-vr-engineer",
        "total_count": null
      }
    ],
    "kra_match_roles": [
      {
        "display_name": "DevOps Engineer",
        "matched_count": null,
        "role_id": 10,
        "score": 0.3918,
        "slug": "devops-engineer",
        "total_count": null
      },
      {
        "display_name": "Cloud Architect",
        "matched_count": null,
        "role_id": 9,
        "score": 0.3878,
        "slug": "cloud-architect",
        "total_count": null
      },
      {
        "display_name": "Android Engineer",
        "matched_count": null,
        "role_id": 4,
        "score": 0.3784,
        "slug": "android-engineer",
        "total_count": null
      },
      {
        "display_name": "Data Engineer",
        "matched_count": null,
        "role_id": 2,
        "score": 0.3779,
        "slug": "data-engineer",
        "total_count": null
      },
      {
        "display_name": "ML Engineer",
        "matched_count": null,
        "role_id": 3,
        "score": 0.3438,
        "slug": "ml-engineer",
        "total_count": null
      }
    ],
    "skill_match_roles": [
      {
        "display_name": "Backend Engineer",
        "matched_count": 4,
        "role_id": 1,
        "score": 0.1818,
        "slug": "backend-engineer",
        "total_count": 22
      },
      {
        "display_name": "Data Engineer",
        "matched_count": 4,
        "role_id": 2,
        "score": 0.1818,
        "slug": "data-engineer",
        "total_count": 22
      },
      {
        "display_name": "Cybersecurity Engineer",
        "matched_count": 3,
        "role_id": 5,
        "score": 0.1364,
        "slug": "cybersecurity-engineer",
        "total_count": 22
      },
      {
        "display_name": "ML Engineer",
        "matched_count": 2,
        "role_id": 3,
        "score": 0.0909,
        "slug": "ml-engineer",
        "total_count": 22
      },
      {
        "display_name": "Cloud Architect",
        "matched_count": 2,
        "role_id": 9,
        "score": 0.0909,
        "slug": "cloud-architect",
        "total_count": 22
      }
    ],
    "stage35_ran": false
  },
  "stage4_decision": {
    "alias_collision_detected": false,
    "case": "E",
    "chosen_role": null,
    "confidence": 0.0,
    "llm2_fired": false,
    "llm2_reasoning": null,
    "queued": true,
    "reasoning": "low_kra: top KRA 0.39 \u003c 0.4"
  },
  "stage5_updates": {
    "centroid_n_after": null,
    "centroid_updated": false,
    "collision_log_id": null,
    "new_kra_attached": null,
    "new_skills_attached": [],
    "queue_entry_id": 34,
    "v3_pipeline_triggered": false,
    "v3_role_slug": "sr.-gcp-data-engineer",
    "v3_run_id": "DRY_RUN"
  }
}
API 2 — extract-details
{}
API 3 — final-role-output
{}

LLM Calls

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

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