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