What You’ll Do

• Lead, mentor, and coach a cross-functional team of data scientists and data engineers; monitor work assignments, track milestones, and hold staff accountable for the quality and timeliness of deliverables 
• Manage stakeholder expectations by proactively communicating progress, risks, and trade-offs to technical and non-technical audiences 
• Drive the end-to-end engineering lifecycle, including feature engineering, model architecture and design, training, validation, deployment, and monitoring 
• Architect scalable, resilient data pipelines using Microsoft Fabric native orchestration tools and lead data modeling and warehousing efforts, leveraging medallion architecture and Fabric Lakehouse 
• Establish and enforce engineering standards for ETL/ELT processes, code quality, version control, CI/CD, and security, including row-level and object-level controls 
• Participate in and lead Agile ceremonies; accurately estimate assignments and maintain technical documentation 
• Assist with interviewing and onboarding new team members to ensure team sustainability 

What We’re Looking For

• Data Engineering Proficiency: Expert-level understanding of ETL/ELT pipelines, data warehousing, medallion architecture and orchestration tools; prior experience leading data engineering teams building enterprise-scale data platforms 
• Knowledge and Understanding of Data Science: Exposure to ML model architecture and design, including supervised and unsupervised learning, deep learning, NLP, and time-series forecasting; prior experience working with data science teams desired 
• Leadership & Accountability: Proven ability to set clear expectations, monitor deliverables, provide constructive feedback and hold team members accountable; skilled at managing stakeholder expectations across technical and business audiences 
• Problem-Solving & Communication: Strong analytical skills with the ability to break down complex problems and develop effective solutions; effectively articulate ideas and collaborate across cross-functional teams 

• Programming
  • Python (expert), T-SQL (advanced), Spark/PySpark (advanced)
• Data Engineering
  • ETL/ELT pipelines (expert), data modeling (advanced), data warehousing (expert), Medallion Architecture
• ML & Data Science
  • Knowledge and experience executing and monitoring machine learning models
• Platforms & Tools
  • Microsoft Azure and Fabric, Lakehouse, OneLake, semantic models (advanced), Power BI reporting
• Cloud & Security
  • Azure compute, storage databases and developer tools (advanced); row-level and object-level security; performance monitoring and optimization
• DevOps & Process
  • Azure DevOps Git, CI/CD pipelines, RESTful APIs, agile/scrum, Microsoft Power BI

Desired Skills

• Cloud cost optimization strategies 

• Cross-tenant data sharing and Microsoft Power BI/semantic model sharing in Microsoft Fabric 

• Observability tooling and platform monitoring 

• Knowledge of project management and financial concepts, including budgets, revenue, profit and earned value 

• Certifications in Microsoft Azure, Python, Fabric or SQL desired 

Bachelor’s degree in computer science, data science, statistics, mathematics or a related field; master’s degree preferred; 7+ years in data engineering and/or data science, with at least 3 years in a technical leadership role overseeing cross-functional data teams 

Director, Engineering

10–15 (data scientists, data engineers and full stack engineers) 

Up to 5%

Exempt

This job operates in a professional office environment. This role routinely uses standard office equipment such as computers, phones, photocopiers, filing cabinets and fax machines.