What the job involves
The main requirements, responsibilities and hiring steps.
Requirements
- 10+ years of IT experience with strong focus on Data Engineering and Cloud Architecture
- 5+ years of hands-on Azure Data Platform experience
- Strong experience in Healthcare domain implementations
- Hands-on expertise in Azure Data Factory Azure Databricks Azure Synapse Analytics Azure Data Lake Storage Azure SQL Database Azure Functions Azure DevOps Azure Monitor and Microsoft Purview
- Strong expertise in SQL and Python/PySpark
- Experience building enterprise-grade ETL/ELT pipelines
- Strong understanding of data modeling and distributed data processing
- Experience with Delta Lake and Lakehouse architectures
- Knowledge of batch and streaming data processing
- Experience implementing enterprise Data Quality frameworks
- Strong understanding of data validation reconciliation profiling and monitoring
- Experience with DQ tools or custom frameworks
- Understanding of data governance and observability
- Knowledge of healthcare data models and workflows
- Understanding of EMR/EHR claims patient provider and clinical data
- Familiarity with healthcare compliance and data privacy standards
- Bachelor’s or Master’s degree in a related field
Nice to have
- Client-facing consulting experience
- Agile/Scrum familiarity
- AI/ML healthcare exposure
- Cloud governance knowledge
- Security framework exposure
Day to day
- Lead the design and implementation of scalable secure Azure healthcare data platforms.
- Architect end-to-end data solutions for ingestion transformation storage governance and analytics.
- Work closely with healthcare stakeholders analytics teams and engineers to deliver enterprise cloud data transformation initiatives.
- Build and optimize ETL/ELT pipelines using Azure Databricks SQL and Python for batch and real-time processing.
- Define and implement data quality controls monitoring and governance practices that improve trust reliability and compliance.