Job SummaryWe are seeking an experienced Data Engineer - Cloud and Healthcare Data Platforms to design, develop, and manage scalable healthcare data pipelines, cloud-based data platforms, and enterprise data integration solutions. This role will focus on data engineering, cloud platform modernization, data migration, and healthcare data interoperability within regulated environments. The ideal candidate will possess strong expertise in SQL, Python, cloud data platforms, ETL/ELT development, and healthcare data standards.
Key Responsibilities- Design, develop, implement, and maintain scalable ETL/ELT pipelines across cloud platforms including Azure, GCP, and AWS.
- Architect and modernize healthcare data acquisition, ingestion, transformation, and integration pipelines.
- Develop and maintain cloud-based data lakes, data warehouses, and analytical data platforms.
- Implement data storage solutions with appropriate partitioning, security, governance, and lifecycle management policies.
- Plan and execute data migration initiatives across platforms and enterprise systems while ensuring data integrity and regulatory compliance.
- Design schemas and data models to support migration of transactional systems into analytical and warehouse environments.
- Integrate new data sources and develop ingestion frameworks for structured and unstructured healthcare data.
- Develop and maintain REST API integrations for data ingestion and interoperability.
- Collaborate with business stakeholders and technical teams to translate business requirements into scalable technical solutions.
- Define and maintain data models, data lineage documentation, standards, and Service Level Agreements (SLAs).
- Provide technical mentorship and guidance to engineering and project teams.
- Support orchestration, automation, monitoring, and optimization of enterprise data workflows.
- Ensure compliance with data governance, privacy, and healthcare regulatory requirements.
- Contribute to continuous improvement initiatives related to platform scalability, performance, and operational reliability.
Required Qualifications- Minimum 5 years of hands-on data engineering experience.
- Expert-level proficiency in SQL including advanced querying techniques such as correlated subqueries and window functions.
- Strong Python development experience for data pipelines, automation, and API integrations.
- Experience with Python libraries such as pandas, numpy, and SQLAlchemy.
- Experience with ETL and transformation tools such as Azure Data Factory, GCP Dataproc, Dataflow, SSIS, or dbt.
- Experience with workflow orchestration tools.
- Experience consuming and integrating REST APIs for data ingestion and interoperability.
- Proficiency with version control systems such as Git.
- Familiarity with R for statistical analysis and data manipulation.
- Familiarity with Python machine learning libraries.
- Strong analytical, troubleshooting, and problem-solving skills.
- Excellent written and verbal communication skills.
- Ability to manage multiple priorities and deadlines effectively.
- Ability to maintain confidentiality and exercise sound judgment when handling sensitive information.
- Strong collaboration and teamwork skills.
Preferred Qualifications- Bachelor's degree in Computer Science, Engineering, Data Engineering, or a related field.
- Experience working within HIPAA-regulated environments and healthcare data privacy requirements.
- Experience with healthcare data exchange standards including HL7 v2/v3 and FHIR.
- Experience implementing cell suppression and statistical disclosure methodologies using SQL.
- Familiarity with SAS.
- Experience supporting enterprise healthcare analytics and data modernization initiatives.
