Data Engineer

Job Summary

Client is looking for Data Engineer

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.

Qualifications

• 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.

Skills 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.