Data Engineering Supervisor (100% Remote)

Summary: 

The Data Engineering Supervisor is responsible for leading and growing the Data Engineering team. This role serves as a people leader and technical authority within the Data Engineering organization, responsible for guiding a team of Data Engineers in the design, implementation, and optimization of enterprise-scale data solutions built on Microsoft Fabric. The Data Engineering Supervisor establishes and enforces engineering standards, drives consistency across the data platform, and ensures the team delivers reliable, scalable, and secure data solutions that support operational reporting, advanced analytics, machine learning, and enterprise decision-making. 

In addition to leadership responsibilities, this role maintains hands-on technical involvement, collaborating with business stakeholders, analytics teams, architects, and senior leadership to align platform strategy with organizational goals.  

What This Role Does:  

Leads, mentors, and develops a team of Data Engineers through regular 1:1s, performance feedback, code reviews, design reviews, and ongoing coaching to build individual and team capability. 

Sets and enforces data engineering standards, development frameworks, reusable patterns, and operational best practices to ensure consistency, quality, and scalability across the data platform. 

Owns team capacity planning, workload prioritization, and delivery execution across active engineering initiatives. 

Collaborates with cross-functional teams, including analytics, architecture, and business stakeholders to understand requirements and translates them into effective Microsoft Fabric–based data solutions. 

Serves as the escalation point and technical decision-maker for complex engineering challenges, production incidents, and architectural decisions. 

Leads root cause analysis and resolution efforts for critical production issues impacting enterprise data pipelines, reporting solutions, and platform operations. 

Reviews and approves solution designs, architecture decisions, and implementation approaches to ensure alignment with enterprise standards. 

Designs, develops, and maintains end-to-end data ingestion and transformation processes using Microsoft Fabric OneLake, Lakehouses, Data Pipelines, Dataflows Gen2, and Notebooks. 

Formats, cleanses, and stores data in a structured manner following Medallion Architecture to ensure data quality and accessibility for reporting and analysis. 

Works closely with reporting and analytics teams to ensure datasets are accurate, well-modeled, and optimized for Power BI and other analytical workloads. 

Participates in data governance activities to ensure data integrity, security, and compliance. 

Evaluates emerging technologies, industry trends, and architectural patterns and provides recommendations for adoption to senior leadership. 

Manages and optimizes Microsoft Fabric platform performance, including capacity utilization, query performance, Delta table maintenance, data partitioning, and pipeline execution. 

Develops and maintains monitoring, alerting, and observability solutions for Microsoft Fabric pipelines, Lakehouses, Warehouses, semantic models, and related components. 

Provides ancillary support for Machine Learning (ML) and Artificial Intelligence (AI) processes. 

Creates comprehensive documentation for data pipelines, engineering standards, and platform architecture. 

Takes an active approach to talent management by overseeing onboarding, recruitment, succession planning, and employee development to build and sustain a diverse, highly engaged, and skilled Data Engineering team. 

Performs other duties as assigned. 

What You Will Bring: 

Bachelor's degree in computer science, information technology, or a related field. Equivalent combinations of education and relevant experience will be considered. 

A minimum of 10 years of combined experience in data engineering and/or software engineering. 

A minimum of three (3) years of demonstrated experience leading, supervising, or managing a team of engineers, including performance management, mentorship, and career development. 

Proven ability to set engineering standards, governance processes, and development frameworks across a data engineering organization. 

Strong hands-on experience with Microsoft Fabric, including OneLake, Lakehouses, Data Pipelines, Dataflows Gen2, and/or Notebooks. 

Solid understanding of Medallion Architecture, Delta Lake concepts, data modeling, and modern analytics patterns. 

Experience establishing and enforcing CI/CD practices, source control strategies, and release management processes. 

Experience with data governance, data quality, and data security frameworks and standards. 

Expertise in integrating Fabric solutions with Power BI, Azure services, and external data sources. 

Advanced troubleshooting and performance optimization experience across cloud data platforms and enterprise data solutions. 

Experience with Git-based source control and collaborative development workflows. 

Experience with Apache Spark and PySpark within Microsoft Fabric. 

Demonstrated ability to lead through influence, including leading initiatives or workstreams, contributing to best practices, and driving cross-functional outcomes. 

Respectful and outstanding leadership skills that motivate colleagues to focus their energy on achieving business goals. 

Ability to plan and manage at both strategic and tactical operational levels. Works to achieve goals while overcoming obstacles and/or planning for contingencies. 

Strong analytical, planning, and budgeting skills. 

Excellent verbal and written communication skills with the ability to present technical concepts clearly to both technical and non-technical audiences. 

Self-starter with strong organizational and time management skills; able to handle multiple priorities with demanding timeframes. 

Ability to work independently and collaboratively in a high-quality, results-driven, team-oriented, fast-paced environment. 

Demonstrated ability to use discretion, make sound decisions, and maintain confidentiality. 

Willingness and ability to work flexible hours as needed. 

Proficiency in MS Office (including Excel, Outlook, PowerPoint, Visio, & Word) and modern communication tools for virtual teams (e.g., MS Teams, Slack). 

Preferred: 

Expertise in developing data pipelines to support Machine Learning (ML) and/or Artificial Intelligence (AI) tools. 

Physical Demands: 

In accordance with the Americans with Disabilities Act (ADA) and applicable state and local laws, the Company will provide reasonable accommodations to qualified individuals with documented disabilities to enable them to perform the essential functions of the job, unless such accommodations would impose an undue hardship. Employees seeking accommodation should contact the People Department to initiate the interactive process. 

Employees may experience the following physical demands for extended periods of time:  

Sitting, standing, and walking (90-100%) 

Keyboarding (95-100%) 

Viewing computer monitor, tablet, and cell phone requiring close vision (70-90%) 

Work Environment: 

100% Remote: Work environment is at home.