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Metro location, popular data-engineer title, and broad platform skillset increase applicant competition.
Core data engineering skills transfer across industries, but insurance governance and Snowflake platform expertise raise domain specificity.
Explicit 7+ years, deep platform ownership, and specific stack requirements enforce strict shortlist filtering.
Build and operate internal data platforms and distributed workflow systems (e.g., Temporal, Airflow) that support the company’s data stack.
Develop and maintain internal Python libraries and platform applications enabling teams to author and run ingestion and transformation jobs.
Administer key data infrastructure components (Snowflake, dbt Cloud, Airflow, Kafka) with ownership of governance, reliability, monitoring, cost optimization, and incident response.
7+ years of software engineering experience.
Proficient in at least one programming language such as Go or Python.
Experience managing data-intensive or distributed applications and backend systems in production.
Strong skills in SQL, data modeling, ETL, data warehousing, data governance, and software engineering best practices including CI/CD and observability.
Experienced building and operating developer-facing platforms and internal tools for cross-functional engineering teams.
Demonstrated ability in operating distributed workflow systems and deep Snowflake administration including RBAC, data masking, and cost governance.
Comfortable collaborating with software engineering, analytics, operations, and product teams to meet platform and data requirements in a regulated environment.