AWS Data Engineer

Interview Mode: Final interview is face to face in Beverly Hills, CA

Must-Have Experience

Candidates should demonstrate 10 + years of data engineering experience with depth in:

• Cloud data warehouse / lakehouse — Amazon Redshift or Databricks. Real production ownership: modeling, performance tuning, cost management, workload isolation.
• Python
• Apache Airflow — authoring and operating DAGs at scale; dependency management, retries, SLAs, observability.
• dbt — model design, testing, macros, documentation, CI/CD for transformations.
• Data movement / ingestion tooling — e.g. Fivetran, Airbyte, AWS DMS, Kafka/Kinesis, or custom CDC and API ingestion frameworks.
• Open table formats — Apache Iceberg / Delta Lake / Hudi . Partitioning, schema evolution, compaction, time travel.
• Apache Spark — PySpark or Spark SQL for large-scale batch/streaming transformation.
• SQL — advanced, including window functions and query optimization.
• Data Governance & Data quality & observability tooling (Great Expectations, Monte Carlo, Elementary)