Azure Data Engineer with Healthcare domain exp

Role: Azure ETL Data Engineer

Location: McLean VA 22102 (100% Onsite) - Need candidates local to / in & around McLean VA as we have In-person client interview

Type of Hire: C2C

We would need candidates local to work location as there will be mandatory In-person client interview and candidate will have a in depth coding interview during In-person interview.

Please look for candidate who has experience in Healthcare clients.

Key Responsibilities

• Design develop and maintain scalable data pipelines using Azure Data Factory / Azure Data Pipelines (ADT).
• Build and optimize ETL workflows to extract transform and load data from multiple structured and unstructured sources.
• Develop data integration services and backend components (C#).
• Write and optimize complex SQL queries stored procedures and performance-tuned database solutions.
• Implement data quality checks validation frameworks and monitoring dashboards.
• Work with cross-functional teams (Data Analysts Architects DevOps) to understand data needs and deliver robust solutions.
• Ensure data security compliance and governance across pipelines and storage layers.
• Troubleshoot data pipeline issues and drive root-cause analysis and resolutions.
• Contribute to architecture discussions and recommend improvements for performance scalability and cost efficiency.

Required Skills & Qualifications

• 8 years of professional experience as a Data Engineer or similar role.
• Strong programming skills / C# for backend or data integration components.
• Deep expertise in SQL including query optimization indexing stored procedures and relational database concepts.
• Proven experience building ETL pipelines and data workflows.
• Hands-on experience with Azure Data Factory / Azure Data Pipelines (ADT) (heavy/advanced experience required).
• Knowledge of Azure storage services such as Azure SQL DB Synapse Data Lake Storage (ADLS) Blob Storage.
• Familiarity with CI/CD pipelines Git and deployment automation.
• Understanding of data modeling concepts (star schema snowflake SCD normalization).