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.