Lead Engineer, Big Data (ai/azure Data Services) - Remote

Lead Data Engineer

A Lead Data Engineer collaborates with the Data Quality and Governance team to ensure data pipelines, data integrity, and compliance by defining data strategies, implementing Data Governance capabilities, creating self-service data assets, and integrating robust data quality and governance frameworks to support trustworthy AI solutions. Key responsibilities include designing scalable data architectures, establishing data quality standards and monitoring, managing data lineage, and ensuring adherence to regulatory requirements and privacy policies.

Knowledge, Skills & Abilities (Occupational knowledge and specific technical and professional skills and abilities required to perform the essential duties of this job):

• Data Quality & Governance Leadership
• Regulatory Compliance & Security
• Data Architecture & Lifecycle Management
• AI/ML Enablement
• Cross-Functional Collaboration
• Lead by Example
• Leadership & Mentorship

Job Function:

Responsible for all the aspects of architecture, design and implementation of Data Governance in Databricks

Required Education:

Bachelor's Degree

Required Experience:

8+ years of data management experience

Prior experience leading projects or teams

Strong experience on Data Lake, Data Warehouse, Data Validation & Certification, Data Quality, Metadata Management and Data Governance

Experience in Azure Data Services (like Azure Databricks, Unity Catalog, Purview, Azure Data Factory) and Power BI, and in programming languages such as PySpark/Python/SQL, etc.

Preferred experience in building stream-processing systems, using solutions such as Kafka, Storm or Spark-Streaming

Experience in implementing AI based solutions in Data Governance space

Preferred Education:

Master's Degree

Preferred Experience:

Experience in the healthcare industry is preferred

Pay Range: $107,028.57 - $208,705.4 / ANNUAL Actual compensation may vary from posting based on geographic location, work experience, education and/or skill level.