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Mid-level, popular Data Engineer title, Bangalore location, and broad platform skillset increase competition.
Data platform skills transfer across industries, but governance and insurance context add some specialization.
Explicit 4+ years requirement plus mandatory platform, language, and Snowflake ownership raises filter strictness.
Build and operate internal data platforms, distributed workflow systems (Temporal, Airflow), and platform applications including config-driven UIs for ingestion and transformation jobs.
Write and maintain internal Python libraries and own data infrastructure administration across Snowflake, dbt Cloud, Airflow, Kafka focusing on governance, reliability, and cost.
End-to-end ownership of production code including design, deployment, operation, incident response, and automation of workflows and ML model deployment.
4+ years of software engineering experience.
Proficiency in programming languages such as Go or Python.
Experience building and maintaining backend systems, internal tools, or platform applications in production.
Proficiency in SQL, data modeling, ETL, data warehousing, and data governance principles.
Experienced with distributed data applications and workflow orchestration platforms, preferably Temporal and Airflow.
Skilled in building developer-facing platforms and working closely with engineering, analytics, product, and operations teams.
Familiarity with administering Snowflake, managing data governance, cost optimization, and operating data infrastructure in production environments.