Build and maintain reliable data ingestion, transformation, and modeling pipelines using Python, Dagster or Airflow, dbt, Snowflake, Airbyte, and AWS. Responsibilities include API and PostgreSQL extracts, Parquet and Snowflake loads, production monitoring, troubleshooting, backfills, incremental modeling, code reviews, Terraform updates, documentation, and runbooks. Partner with analytics and product teams on dimensional modeling, data quality, and pipeline reliability.

Develops and optimizes distributed genomic data pipelines using Hadoop, Spark, Hive, Impala, SQL, and ETL workflows. Integrates genomic, laboratory, epidemiological, and public health datasets from external repositories, ensuring data quality, governance, security, and reproducibility. Collaborates with bioinformaticians, epidemiologists, and laboratory scientists to support pathogen genomics, outbreak detection, surveillance, and situational awareness. Maintains version-controlled pipelines, documentation, data lineage, reports, and scientific communications. This is an on-site role in Atlanta with weekly team meetings.