Hybrid Lead Data Engineer

Posted last week

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About the role

  • Design, build, and maintain scalable ETL pipelines for ingesting and transforming large volumes of data
  • Implement automated data validation, monitoring, and alerting to ensure quality and reliability
  • Integrate diverse internal and external data sources into unified, queryable datasets
  • Optimize storage and query performance for analytical workloads
  • Collaborate with data scientists to productionize ML models and ensure they run reliably at scale
  • Work with product and engineering teams to meet data needs for new features and insights
  • Maintain cost efficiency and operational excellence in cloud environments
  • Build robust ingestion, cleanup, and integration pipelines to ensure accurate, reliable data ready for analysis

Requirements

  • 4+ years of experience in data engineering, ideally in AI, SaaS, or data-intensive products
  • Strong fluency in Python and SQL
  • Experience with modern data modeling tools such as dbt
  • Experience with data warehouses and OLAP databases (e.g., Redshift, Snowflake, BigQuery, ClickHouse)
  • Proven ability to design and maintain production-grade data pipelines in cloud environments (AWS, GCP, or similar)
  • Familiarity with orchestration frameworks (Airflow, Dagster, Prefect)
  • Comfort operating in fast-paced, ambiguous environments where you ship quickly and iterate

Benefits

  • Equity in a fast-growing startup
  • Competitive benefits package tailored to your location
  • Flexible time off policy
  • Generous parental leave
  • A fun-loving and (just a bit) nerdy team that loves to move fast!

Job title

Lead Data Engineer

Job type

Experience level

Senior

Salary

Not specified

Degree requirement

No Education Requirement

Location requirements

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