• Build and maintain ETL/ELT pipelines using Python and SQL • Develop ingestion workflows with AWS Firehose , S3, and related services • Create and optimize dbt models, tests, and incremental logic • Tune Snowflake queries and warehouse usage for cost and performance • Operate and improve Airflow DAGs for reliable execution and monitoring • Maintain high data quality, data integrity, and pipeline SLA commitments • Bring clarity to ambiguous requirements and propose practical solutions • Lead data engineering best practices and influence architectural decisions • Drive projects independently, from definition to delivery • Collaborate with engineering, analytics, and ML teams to support shared goals • Build feature pipelines to support ML workflows • Support model deployment, monitoring, and automated retraining • Add data validation and quality checks across ML and analytics pipelines