Data Engineer, Louisiana, LA, US
Data Engineer
The scope of the proposed services will include the following:
- Assess feasibility and technical requirements for LINKS → DataLake integration.
- Collaborate with OPH Immunization Program, OPH Bureau of Health Informatics and STChealth on data specifications and recurring ingestion pipelines.
- 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.