Data Engineer

About this role

Analytics Co builds real-time analytics infrastructure for e-commerce and logistics clients. You'll be part of the data platform team responsible for ingestion, transformation, and serving layers across a stack processing ~2 billion events per day.

You'll own end-to-end pipeline development: designing schemas, writing dbt models, building Airflow DAGs, and debugging Spark jobs in production. The team is small (5 data engineers) and ownership is broad.

We're in a period of significant platform migration — moving from a batch-heavy architecture to a streaming-first model using Flink. If you're interested in working on that migration, this is an opportunity to own a significant part of it.

What we're looking for

• ✓3–5 years of data engineering experience in production environments
• ✓Strong Python; you write clean, tested, reviewable code
• ✓Hands-on experience with dbt and Airflow (or equivalent orchestration)
• ✓Familiarity with Spark at scale — you understand partitioning, skew, and query planning
• ✓Experience with cloud data warehouses (BigQuery, Snowflake, Redshift)
• ✓Bonus: experience with Flink or Kafka Streams for real-time processing

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