Design, build, and optimize ETL/ELT pipelines in Azure cloud environments.
Develop scalable and reliable data workflows using Azure Data Factory (ADF) and other Azure data services.
Build and maintain data solutions leveraging Azure SQL and related cloud-native services.
Design and implement robust data models to support analytics, reporting, and downstream integrations.
Develop and support API-based integrations across internal and external systems.
Implement data models following modern Data Lakehouse or layered architecture principles.
Ensure data quality, consistency, and performance across ingestion, staging, and curated layers.
Collaborate with data architects, analysts, and business stakeholders to translate healthcare data requirements into scalable technical solutions.
Develop reusable data transformation logic and modular processing components.
Support deployment processes following CI/CD and DevOps best practices.
Monitor and optimize data workflows for performance, scalability, and reliability.
Contribute to data governance, security, and compliance practices relevant to healthcare environments.

Hands-on experience with Azure Data Services.
Experience building and maintaining data pipelines using Azure Data Factory (ADF).
Strong working knowledge of Azure SQL and relational databases.
Experience with API integrations and cloud-based data workflows.
Solid understanding of Data Modeling concepts for analytics and reporting.
Strong proficiency in SQL.
Experience designing and supporting ETL/ELT processes in cloud environments.
Familiarity with modern data architecture concepts, such as data warehousing, lakehouse, or layered data models.
Ability to work with large datasets and build scalable, reliable data solutions.

Data Engineer – Azure, SQL

Key skills