Data Engineer (SQL, PySpark, Snowflake, DBT, Redshift) - Associate

📋 Description

• Design, build, and operate scalable, production‑grade data platforms on AWS.
• Own end-to-end data pipelines from ingestion to governance in a lakehouse stack.
• Develop and run Spark and AWS Glue ETL/ELT jobs for diverse data sources.
• Model, load, and optimize data in Snowflake; govern assets via data catalogs.
• Architect and implement AWS data solutions (S3, Glue, EMR, Lambda, Athena, Kinesis, Redshift, IAM).
• Ensure data quality, lineage, security, and cost efficiency across environments.

🎯 Requirements

• 5 to 8 years of hands‑on data engineering experience building production data pipelines.
• Strong Python for data engineering and automation; advanced SQL with relational DBs.
• Experience with a data pipeline orchestrator (Airflow, Dagster, or equivalent).
• Hands‑on Spark experience and production use of Apache Iceberg for lakehouse storage.
• AWS Glue ETL, Glue Data Catalog; Snowflake data warehouse experience.
• Experience with AWS services (S3, EMR, Lambda, Athena, Kinesis, Redshift, IAM).

🎁 Benefits

• Equal opportunity employer.
• Reasonable accommodations available during application/interview process.
• Careers page and contact options provided for accommodations.