Data Engineering Lead

Oxford Global Resources is seeking a hands-on Data Engineering Lead to guide its data engineering team and shape its enterprise data platform. The role leads a team while overseeing platform strategy across Azure and Microsoft Fabric, engineering delivery, reliability, and collaboration with analytics, technology, and business stakeholders.

Responsibilities:

• Lead, mentor, and develop a team of data engineers through clear priorities, project planning, code reviews, coaching, and career development
• Own the platform strategy across Azure and Microsoft Fabric, identifying overlapping pipelines, storage, and tooling and creating a practical roadmap to consolidate or retire redundant components
• Build and mature Oxford’s Microsoft Fabric platform, including Lakehouse, Warehouse, Data Factory pipelines, and OneLake, while defining what should remain in Azure and what should move into Fabric
• Develop complex T-SQL queries, stored procedures, and database solutions while managing, monitoring, and optimizing SQL Server database environments for performance, reliability, and scalability
• Design, optimize, test, and maintain the stored procedures that support Oxford’s core ETL processes, with disciplined version control and performance management
• Manage transformation pipelines end to end, including orchestration, scheduling, monitoring, failure handling, troubleshooting, and recovery
• Lead impact analysis and change management for major upstream source-system changes, coordinating with platform owners and downstream stakeholders so the warehouse adapts before the business is disrupted
• Establish and reinforce standards for data quality, testing, observability, documentation, security, and CI/CD
• Partner with analysts, BI developers, technical teams, and business stakeholders to translate requirements into reliable, scalable data products
• Manage platform reliability, performance, and cloud cost while applying sound governance practices around access, lineage, compliance, and PII handling
• Evaluate emerging tools and approaches, make clear build-versus-buy recommendations, and communicate priorities, risks, tradeoffs, and progress to technical and nontechnical leaders

Requirements:

• Five or more years of data engineering experience, including at least two years leading engineers formally or as a technical lead
• Strong, hands-on experience using Microsoft Fabric in a production environment, beyond evaluation or proof-of-concept work
• Working knowledge of Azure data services, including Azure Data Factory, Synapse, ADLS Gen2, and Azure SQL, and how those services integrate with or overlap Microsoft Fabric
• Advanced T-SQL skills, including experience writing, tuning, testing, and maintaining stored procedure-based ETL at scale
• Experience orchestrating and monitoring transformation pipelines, with a demonstrated ability to diagnose and resolve production failures
• Proficiency in Python and working knowledge of Spark or PySpark
• A strong foundation in dimensional and lakehouse or medallion data modeling, along with modern ETL and ELT design patterns
• Experience with CI/CD and infrastructure as code, using tools such as Azure DevOps or GitHub Actions and Terraform or Bicep
• Clear communication, sound judgment, and the ability to influence stakeholders while balancing hands-on delivery with team leadership
• Microsoft Certified Fabric Analytics Engineer Associate DP-600 or Fabric Data Engineer Associate DP-700 certification
• Experience managing data from enterprise source platforms such as Salesforce, ATS or VMS platforms, and ERP or finance systems, ideally in staffing or business services
• Experience leading a data-platform migration or consolidation
• Familiarity with applying AI to the data estate, including grounding large language models and natural-language query tools in governed semantic models and evaluating the accuracy of AI-generated answers