Data Engineer (Gov Exp Required)

Remote but may require onsite visit once in 3 months 3 professional References The scope of the proposed services will include the following: • Assess feasibility and technical requirements for LINKS → DataLake integration. • Build and optimize ETL workflows for LINKS and complementary datasets (Vital Records, labs, registries). • Design scalable data workflows to improve data quality, integrity, and identity resolution. • Implement data governance, observability, and lineage tracking across all pipelines. • Mentor engineers, support testing, and enforce best practices in orchestration and architecture. • Document and communicate technical solutions to technical and non-technical stakeholders. Expertise and/or relevant experience in the following areas are mandatory: • 3 years of experience in data engineering and/or data architecture • 2 years of experience with Python for ETL and automation (pandas, requests, API integration). • 2 years hands-on experience with SQL queries, stored procedures, performance tuning (preferable Oracle, SQL Server, MySQL) • 1 year experience with ETL orchestration tools (Prefect, Airflow or equivalent). • 1 year experience with cloud platforms (Azure, AWS, or GCP), including data onboarding/migration. • 1 year exposure to data lake / medallion architecture (bronze, silver, gold) • 2 years of experience providing written documentation and verbal communication for cross-functional collaboration. Expertise and/or relevant experience in the following areas are desirable but not mandatory: • 5+ years of experience in data engineering roles • Experience integrating or developing REST/JSON or XML APIs • Familiarity with CI/CD pipelines (GitHub Actions, Azure DevOps, etc.). • Exposure to Infrastructure as Code experience (Terraform, CloudFormation). • Experience with data governance and metadata tools (Atlan, OpenMetadata, Collibra). • Public health/healthcare dataset or similar experience, including PHI/PII handling. • Familiarity with SAS and R workflows to support epidemiologists and analysts. • Experience with additional SQL platforms (Postgres, Snowflake, Redshift, BigQuery). • Familiarity with data quality frameworks (Great Expectations, Deequ). • Experience with real-time/streaming tools (Kafka, Spark Streaming). • Familiarity with big data frameworks for large-scale transformations (Spark, Hadoop). • Knowledge of data security and compliance frameworks (HIPAA, SOC 2, etc.). • Agile/SCRUM team experience.