Design, build, and operate scalable data pipelines on AWS
Own end-to-end pipeline orchestration, scheduling, retries, and observability
Develop lakehouse assets on Apache Iceberg with partitioning and schema evolution
Develop and operate Spark jobs, including AWS Glue Spark jobs
Model, load, and optimize data in Snowflake and govern assets
Architect data solutions on AWS using S3, Glue, EMR, Lambda, Athena, Kinesis, Redshift

🎯 Requirements

8+ years of hands-on data engineering experience
Strong Python for data engineering and automation
Advanced SQL and relational DBs (PostgreSQL/MySQL)
Experience with a production workflow orchestrator (Airflow/Dagster)
Hands-on Spark for large-scale processing
Experience with Apache Iceberg and lakehouse storage

🎁 Benefits

Collaborative, fast-paced environment
Mentor junior engineers and drive standards
Generative AI tooling and platform improvements

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