Design, implementation, and deployment of enterprise-scale data management, data analytics, and AI capabilities.
Partner with enterprise architecture & engineering to define data and AI roadmaps that align with business objectives and operating models.
Provide technical leadership and mentorship to technical teams while establishing standards.
Lead end-to-end technical delivery for multiple initiatives—from discovery and design through build, test, release, and operations.
Define technical work breakdown structures, estimates, and resource plans.

Requirements

7+ years of hands-on experience in data engineering, analytics engineering, and/or AI application development in enterprise environments.
Deep understanding of data modeling frameworks: Kimbal, EDW Streaming and Lakehouse Architecture.
Expertise with Microsoft Fabric: OneLake, Data Factory, Lakehouse, Warehouse, Real-Time Intelligence/KQL, and Power BI semantic models.
Expertise with Microsoft AI Foundry: model catalog, Agent Service, evaluations/observability, safety/guardrails, and Control Plane.
Proficiency in SQL, Python, and KQL;
Strong understanding of data governance, privacy, and security (RBAC, sensitivity labels, row-level/object-level security, DLP).
Must possess a valid driver’s license and have active personal automobile liability insurance by the first day of employment.

Benefits

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

data engineeringanalytics engineeringAI application developmentdata modeling frameworksSQLPythonKQLdata governancedata privacydata security

Soft Skills

technical leadershipmentorshipcommunicationcollaborationproblem-solving