Job Description

Roles/Responsibilities:

• 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.

Mandatory Skills:

1. 3 years of experience in data engineering and/or data architecture
2. 2 years of experience with Python for ETL and automation (pandas, requests, API integration).
3. 2 years hands-on experience with SQL queries, stored procedures, performance tuning (preferable Oracle, SQL Server, MySQL)
4. 1 year experience with ETL orchestration tools (Prefect, Airflow or equivalent).
5. 1 year experience with cloud platforms (Azure, AWS, or GCP), including data onboarding/migration.
6. 1 year exposure to data lake / medallion architecture (bronze, silver, gold)
7. 2 years of experience providing written documentation and verbal communication for cross functional collaboration.

Desirable Skills:

1. 5+ years of experience in data engineering roles
2. Experience integrating or developing REST/JSON or XML APIs
3. Familiarity with CI/CD pipelines (GitHub Actions, Azure DevOps, etc.).
4. Exposure to Infrastructure as Code experience (Terraform, CloudFormation).
5. Experience with data governance and metadata tools (Atlan, OpenMetadata, Collibra).
6. Public health/healthcare dataset or similar experience, including PHI/PII handling.
7. Familiarity with SAS and R workflows to support epidemiologists and analysts.
8. Experience with additional SQL platforms (Postgres, Snowflake, Redshift, BigQuery).
9. Familiarity with data quality frameworks (Great Expectations, Deequ).
10. Experience with real-time/streaming tools (Kafka, Spark Streaming).
11. Familiarity with big data frameworks for large-scale transformations (Spark, Hadoop).
12. Knowledge of data security and compliance frameworks (HIPAA, SOC 2, etc.).
13. Agile/SCRUM team experience

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