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Medium competition from popular analytics title, Bengaluru metro market, and broad dbt/Snowflake skill requirements.
Low — analytics engineering skills (dbt, Snowflake, SQL/Python) are broadly transferable across industries.
Medium because mandatory dbt, Snowflake, SQL/Python, semantic modeling, and LLM tooling are required.
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Build and maintain dbt transformation pipelines and dimensional data models for clean, analysis-ready datasets.
Design and manage Snowflake Semantic Views and semantic layer for governed, reusable data definitions to support BI and AI-driven querying.
Own data quality, testing, documentation, and certification of datasets to enable trustworthy metrics for downstream consumers such as Looker/Tableau.
Hands-on production experience with dbt including staging/marts patterns, tests, and documentation.
Strong dimensional and semantic data modeling skills (star schemas, facts vs. dimensions, grain, slowly changing dimensions).
Production experience with Snowflake, semantic views, or comparable semantic/metrics layers (LookML, dbt Semantic Layer, MetricFlow, or Cube).
Work Experience Required: Not explicitly mentioned in the JD.
Experienced in translating complex business metric definitions into governed, reusable data models and semantic objects.
Proficient in SQL and Python for data transformation, testing, and tooling.
Comfortable using AI/LLM tools for code generation, query drafting, and model development within daily engineering workflows.