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Remote role with sought-after dbt/Snowflake skills but lesser-known employer yields moderate competition.
Analytics engineering skills (dbt, SQL, Snowflake) are transferable across industries, though domain knowledge helps.
Explicit 6-8+ years, mandatory dbt/Snowflake/SQL/Python and on-call requirements make filters stringent.
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Lead design and maintenance of modular, tested data transformation pipelines using dbt on Snowflake or Databricks, ensuring high performance and cost efficiency.
Own the semantic metrics layer and collaborate with BI teams to deliver consistent, governed data products and dashboards.
Implement and own automated data quality testing and monitoring, supporting ML-ready analytics datasets and providing mentorship to junior engineers.
6-8+ years experience in analytics engineering, data analytics, or data engineering focused on data modeling and transformation.
Expert-level SQL and Python skills with hands-on experience in dbt (Core or Cloud) and Snowflake or Databricks platforms.
Proven lifecycle ownership from design through production deployment of analytics code.
Work Hours: Must be available during critical US overlap hours (roughly 6 AM – 2 PM IST) with on-call rotation for pipeline health monitoring.
Deep expertise in dbt-based analytics engineering with production-grade software engineering rigor and automation focus.
Experience delivering governed semantic layers and curated domain-specific analytics models for Finance, Sales, or Operations.
Comfortable operating in remote, cross-time-zone environments partnering closely with US-based teams and multi-disciplinary stakeholders.