Senior Data Engineer with Healthcare Background-Minneapolis, MN-Hybrid -Need Locals Only

Job title: Senior Data Engineer with Healthcare Background

Location: Minneapolis, MN-Hybrid -Need Locals Only

Longterm

Need 10+ Years EXP Must

Job Summary

We are seeking a highly skilled Senior Data Engineer with strong experience in Azure Data Factory (ADF), Azure Databricks, Synapse Analytics, and Data Lake (ADLS) to support enterprise-scale data initiatives in the Healthcare domain. The ideal candidate will design, build, and optimize cloud-based data pipelines and architectures to enable advanced analytics, reporting, and data-driven healthcare decision-making.

Key Responsibilities

• Design, develop, and implement data pipelines and ETL processes using Azure Data Factory (ADF), Azure Databricks (PySpark), and Synapse Analytics to ingest, process, and store healthcare data from diverse structured and unstructured sources.
• Build and maintain medallion data architectures (bronze-silver-gold layers) to ensure scalability, reusability, and performance across analytics workloads.
• Implement real-time and batch data processing solutions leveraging ADF triggers, Event Hub, Service Bus Queues, and Stream Analytics for timely data delivery and event-driven architectures.
• Collaborate with data analysts, data scientists, and business teams to understand data requirements and translate them into efficient and automated data workflows.
• Integrate data from multiple healthcare systems (EHR, EMR, claims, HL7/FHIR feeds, payer/provider systems, etc.) into centralized Azure Data Lake environments while ensuring compliance with HIPAA and PHI data security standards.
• Develop and manage Linked Services, Datasets, and Data Flows within ADF, optimizing for performance and cost efficiency.
• Utilize PolyBase and Synapse Analytics for large-scale data loading and querying to support downstream BI and Power BI reporting.
• Deploy CI/CD pipelines using Azure DevOps or Jenkins, ensuring automated, version-controlled, and consistent deployment of data integration artifacts.
• Create and maintain technical documentation, data dictionaries, and data lineage to support data governance and traceability.
• Monitor, troubleshoot, and optimize ADF pipelines and Databricks clusters, ensuring system reliability and timely data delivery.
• Support data migration initiatives from on-premises (e.g., Oracle, Teradata, SQL Server) to Azure Data Lake and cloud-native platforms.
• Implement data quality, validation, and audit mechanisms to ensure the accuracy and reliability of healthcare datasets.
• Participate in sprint planning, code reviews, and cross-functional collaboration to deliver high-quality, production-ready data solutions.

Required Skills & Experience

• 10+ years of experience as a Data Engineer, including at least 3+ years in a Healthcare environment.
• Strong proficiency in Azure Data Factory (ADF v2), Azure Databricks (PySpark), Azure Synapse Analytics, and ADLS Gen2.
• Hands-on experience with Azure Event Hub, Service Bus, Logic Apps, and Stream Analytics for real-time and event-driven data integration.
• Advanced SQL skills (T-SQL, PL/SQL) and experience creating stored procedures, triggers, and complex queries for data transformation.
• Experience working with healthcare datasets (EHR/EMR, HL7, FHIR, Claims, Clinical, or Patient Data) and understanding of HIPAA compliance.
• Proven ability to migrate data from on-prem systems (Oracle, Teradata, SQL Server) to Azure cloud environments.
• Experience implementing DevOps CI/CD for data projects using Azure DevOps, Git, or Jenkins.
• Familiarity with data modeling, data warehousing concepts, and dimensional modeling.
• Proficiency in Python, PySpark, and scripting for data automation and transformation.
• Strong analytical, problem-solving, and communication skills with the ability to work cross-functionally with business and technical teams.
• Bachelor s degree in Computer Science, Data Engineering, Information Systems, or related field.

Preferred Qualifications

• Experience in Microsoft Fabric and Power BI integration.
• Exposure to machine learning workflows within Databricks or Azure ML.
• Knowledge of data governance frameworks and metadata management tools.
• Familiarity with FHIR APIs, HL7 data integration, or payers/providers data ecosystems.
• Microsoft Azure certifications (e.g., DP-203: Data Engineering on Microsoft Azure) are a plus.

Regards,

Sai Srikar

Email: