Director of Data Engineering

Duties and Responsibilities:

Own the Microsoft Fabric Platform 

• Serve as the technical owner of JSSI's Microsoft Fabric environment — architecture, governance, performance, and access control 

• Drive the roadmap for the platform including CI/CD enablement, Git integration, and centralized ingestion workspace design 

• Manage Fabric capacity, right-sizing, backup, and disaster recovery 

Build and Maintain Data Pipelines 

• Design, build, and operate reliable data pipelines that connect source systems into clean, usable data 

• Establish monitoring, alerting, and SLA standards for pipeline reliability 

Define the Data Foundation 

• Establish a single source of truth across all systems and acquisitions, ensuring every team is working from the same numbers 

• Build and maintain enterprise semantic models that serve analytics, reporting, and AI use cases 

• Partner with the data governance function to implement Microsoft Purview for cataloging, classification, and data privacy standards 

Enable Analytics and AI 

• Make the analytics team faster by solving data quality and availability issues at the source 

• Build the data foundation that AI initiatives depend on, enabling the organization to move from insight to action 

• Develop and support AI data agents to expand analytics delivery across the organization 

• Responsible for supporting ML initiatives (not just AI agents) 

 Lead and Grow the Team 

• Manage and mentor a team of 2–5 data engineers, setting technical standards and fostering a high-performance culture 

• Partner cross-functionally with analytics, product, and business stakeholders to prioritize and deliver 

• Represent the data engineering function in leadership discussions and help shape JSSI's broader data strategy 

Desired Credentials:

Experience 

• 10+ years of experience in data engineering, with a track record of building and scaling data platforms in production environments 

• 3+ years in a leadership role managing engineers, with demonstrated ability to develop talent and build team culture 

• Experience as a player-coach — comfortable rolling up your sleeves while also setting direction for the team 

 Technical Skills 

• Deep expertise with Microsoft Fabric, including Lakehouse and Warehouse architecture, pipelines, and OneLake 

• Strong hands-on experience with Azure cloud infrastructure and Azure Data services 

• Proficiency in SQL and Python for data engineering and pipeline development 

• Experience designing and implementing ETL pipelines across complex, multi-source environments 

• Familiarity with CI/CD practices and Git-based deployment workflows for data platforms 

• Experience with data governance platforms (Microsoft Purview preferred) and semantic layer design 

• Working knowledge of Power BI and enterprise reporting architectures 

• Familiarity with AI/ML data patterns and building data products that support machine learning use cases 

 Leadership and Collaboration 

• Strong communicator who can translate technical complexity into clear language for business stakeholders 

• Collaborative partner who works well across analytics, product, and business teams 

• High ownership mindset — you treat data as a product and hold yourself accountable for its quality and reliability