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.
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