Full Stack Data Engineer

We're looking for a Full Stack Data Engineer to own our clientsdata platform end-to-end — from ingestion and pipelines to APIs and self-serve analytics. You'll work across the entire data lifecycle, collaborating with Product, Engineering, and Analytics to turn raw data into reliable, scalable products.

What You'll Do

• Build & Scale Pipelines: Design, build, and maintain robust ETL/ELT pipelines using Python, SQL, Spark, and Airflow
• Data Infrastructure: Architect and manage data warehouses/lakehouses on AWS/GCP/Azure — BigQuery, Redshift, Snowflake, or Databricks
• Full Stack Data Products: Develop APIs, data services, and internal tools that let teams access and use data easily
• Data Modeling: Design dimensional models and optimize queries for analytics and ML use cases
• Reliability: Implement data quality, observability, testing, and CI/CD for all data workflows
• Cross-functional Impact: Partner with Analysts, MLEs, and Software Engineers to deliver production data features

What You'll Need

• Experience: 10+ years in Data Engineering, Software Engineering, or similar roles
• Programming: Strong Python and advanced SQL. Go/Java is a plus
• Big Data: Hands-on experience with Spark, Kafka, or Flink
• Orchestration: Airflow, dbt, or Prefect
• Cloud: AWS, GCP, or Azure — you've shipped in prod on at least one
• Warehousing: Deep knowledge of columnar DBs: BigQuery, Snowflake, Redshift, etc.
• System Design: Can design for scale, latency, cost, and reliability
• Mindset: Product-oriented, ownership-driven, and comfortable with ambiguity