Senior Data Engineering Consultant

Lead end-to-end lifecycle of enterprise data engineering including design, development, deployment, and operational support of scalable Azure cloud data platforms.

Drive technical strategy, architecture standards, and modernization initiatives across data platforms, focusing on cloud transformation, data governance, and AI/ML enablement.

Provide leadership and mentorship to engineering teams, ensuring best practices in DevOps, CI/CD, data quality, and production reliability are enforced.

Bachelor's Degree in Computer Science, IT, Engineering, Data Analytics, Mathematics, or related technical field.

Minimum 8 years experience in Data Engineering, Data Warehousing, Integration, and Platform development.

Minimum 5 years hands-on experience with Microsoft Azure data services including Azure Data Factory, Databricks, ADLS Gen2, Synapse Analytics.

Minimum 3 years experience leading technical teams and working with healthcare data or healthcare analytics platforms.

Experienced in enterprise-scale cloud data platform architecture and modernization especially leveraging Azure and related big data technologies.

Strong leadership capability managing teams and driving complex, cross-functional technology initiatives involving healthcare data.

Proficient in designing and operating AI-ready data architectures including GenAI, Lakehouse, and Data Mesh approaches in regulated environments.