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.