Senior Manager - Data Engineering

3M•Maplewood, MN

11h•Onsite

About The Position

3M is seeking a talented and experienced Senior Manager, Data Product Engineering to lead a cross-functional engineering team responsible for designing, building, and operating enterprise data products that enable analytics, AI, and digital business capabilities. You will collaborate with curious, creative, and diverse teams around the world, delivering trusted, scalable, and reusable data products that create measurable business value. As a Senior Manager, Data Product Engineering, you will make an impact by: Leading, coaching, and developing a high-performing team of Data Engineers and Technical Leads, building an engineering culture focused on quality, ownership, automation, and continuous improvement. Owning the end-to-end delivery lifecycle for enterprise data products — from product planning and technical design through development, testing, deployment, production support, and continuous enhancement. Driving engineering best practices including CI/CD, Infrastructure as Code, automated testing, data quality validation, monitoring, data contracts, and documentation. Partnering with business stakeholders, Product Managers, Enterprise Architecture, and Data Governance to translate business capabilities into technical solutions that deliver measurable outcomes. Guiding cloud-native data solutions using Snowflake, Apache Iceberg, AWS, dbt, Python, SQL, APIs, streaming technologies, and data orchestration platforms. Ensuring data products are designed to support AI applications, machine learning, intelligent agents, semantic models, self-service analytics, and real-time operational decision making.

Requirements

Bachelor’s degree in Computer Science, Engineering, Information Systems, or technology field (completed and verified prior to start)
Ten (10) years of experience in Data Engineering, Software Engineering, or Data Platforms in a private, public, government or military environment
Five (5) years leading engineering teams in a private, public, government or military environment

Nice To Haves

Experience delivering enterprise-scale cloud data solutions
Strong knowledge of modern data architectures
Experience with Agile delivery models
Strong communication and executive presentation skills
AWS, Snowflake, Apache Iceberg, Databricks
dbt, Python, Spark, SQL
Kafka or streaming technologies
Data Mesh or domain-oriented architectures
Product operating models
AI and Machine Learning data platforms
Experience operating in a large, global, regulated enterprise environment
Manufacturing, supply chain, or enterprise analytics experience

Responsibilities

Lead, coach, and develop a high-performing team of Data Engineers and Technical Leads
Build an engineering culture focused on quality, ownership, automation, and continuous improvement
Recruit and develop engineering talent
Establish clear goals, career paths, and performance expectations
Foster collaboration across engineering, architecture, product management, and business teams
Own the end-to-end delivery lifecycle for enterprise data products including: Product planning and technical design, Development, testing, and deployment, Production support and continuous enhancement
Ensure products are reliable, well documented, secure, governed, observable, and reusable across the enterprise
Drive engineering best practices including: CI/CD and Infrastructure as Code, Automated testing and data quality validation, Monitoring and alerting, Version control, data contracts, and documentation
Champion modern software engineering practices within data engineering
Partner with Business Product Managers, Domain leaders, Enterprise Architects, Platform Engineering, Data Governance, and Security
Translate business capabilities into technical solutions that deliver measurable outcomes
Own operational health including availability, performance, data freshness, and data quality
Manage incidents, cost optimization, and technical debt
Establish Service Level Objectives (SLOs) and continuously improve platform reliability
Ensure data products are designed to support: AI applications and machine learning, Intelligent agents and semantic models, Self-service analytics and real-time operational decision making