Design, build, and maintain scalable, fault-tolerant data pipelines (batch and/or streaming) for core business and product data.
Ingest data from diverse sources including APIs, databases, event streams, and third-party services, ensuring high data quality and reliability.
Design and manage data models and storage layers (data warehouses, data lakes) that support analytics and downstream use cases.
Partner with analytics, product, and engineering teams to deliver clean, well-documented datasets that enable self-service analytics and experimentation.
Implement monitoring, logging, and alerting to ensure pipeline reliability, performance, and cost efficiency.
Enforce data governance best practices, including access control, privacy, documentation, and data lineage.

3+ years of experience as a Data Engineer, data-heavy Backend Engineer, or similar role.
Strong programming skills in Python and/or TypeScript, with solid SQL proficiency.
Good understanding of data modeling, ETL/ELT concepts, and analytics workflows.
Hands-on experience with data warehouses (e.g. BigQuery, Snowflake).
Experience building and operating production data pipelines.

Data Engineer

Key skills