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Manager Data Analytics Engineer Jobs in Minnesota

Pwc

Data Engineer - Manager

Minneapolis, MN

Industry/Sector Not Applicable Specialism Data, Analytics & AI Management Level Manager & Summary At PwC, our people in data and analytics engineering focus on leveraging advanced technologies and ...

Cargill

Manager, Data Engineering

Saint Paul, MN · On-site

DATA & ANALYTICAL SOLUTIONS: Oversees the development of data products and solutions using big data ... DevOps practices, including code management, CI/CD, and deployment strategies. * DATA GOVERNANCE:

Apogee

Data Platform Engineer

Minneapolis, MN

$80K - $100K/yr

This Data Platform Engineer will fill a critical role in enhancing and supporting the Data ... Configure and implement data management and analytic platform changes * Document data pipeline ...

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Manager Data Analytics Engineer information

What is the difference between Manager Data Analytics Engineer vs Data Analytics Engineer?

AspectManager Data Analytics EngineerData Analytics Engineer
Required CredentialsBachelor's or Master's in Data Science, Analytics, or related field; often leadership experienceBachelor's or Master's in Data Science, Analytics, or related field
Work EnvironmentLeads teams, manages projects, collaborates with stakeholdersDevelops data models, analyzes data, implements solutions
Employer & Industry UsageUsed in tech, finance, healthcare, and large enterprisesCommon in similar industries, often within data teams

The main difference is that a Manager Data Analytics Engineer oversees teams and projects, focusing on leadership and strategic planning, while a Data Analytics Engineer primarily develops and implements data solutions. Both roles require strong technical skills, but the manager role adds a layer of team management and stakeholder communication.

How does a Manager Data Analytics Engineer typically balance technical project work with team leadership responsibilities?

As a Manager Data Analytics Engineer, you are expected to split your time between overseeing complex analytics engineering tasks and guiding your team’s development. This involves setting project priorities, conducting code reviews, and ensuring data solutions align with business goals, while also mentoring team members and facilitating collaboration with stakeholders like data scientists and business analysts. Successful managers often establish clear communication channels and delegate tasks effectively, so they can stay hands-on with key projects while supporting the professional growth of their team.

What are the key skills and qualifications needed to thrive as a Manager Data Analytics Engineer, and why are they important?

To thrive as a Manager Data Analytics Engineer, you need a strong background in data engineering, analytics, and leadership, typically with a degree in computer science or a related field. Familiarity with tools like SQL, Python, data warehousing platforms (e.g., Snowflake, Redshift), and certifications in cloud technologies or data management are common requirements. Excellent communication, problem-solving, and team management skills set top performers apart in this role. These competencies are essential for driving data strategy, ensuring data quality, and leading analytics teams to deliver actionable business insights.

What is a Manager Data Analytics Engineer?

A Manager Data Analytics Engineer is a professional who leads a team of data analytics engineers responsible for designing, building, and maintaining data systems and analytics solutions. They oversee data pipeline development, ensure data quality, and collaborate with stakeholders to translate business requirements into technical solutions. In addition to technical expertise, they manage project timelines, mentor team members, and help drive data-driven decision-making across the organization.
What are the most commonly searched types of Data Analytics Engineer jobs in Minnesota? The most popular types of Data Analytics Engineer jobs in Minnesota are:
What are popular job titles related to Manager Data Analytics Engineer jobs in Minnesota? For Manager Data Analytics Engineer jobs in Minnesota, the most frequently searched job titles are:
What job categories do people searching Manager Data Analytics Engineer jobs in Minnesota look for? The top searched job categories for Manager Data Analytics Engineer jobs in Minnesota are:
What cities in Minnesota are hiring for Manager Data Analytics Engineer jobs? Cities in Minnesota with the most Manager Data Analytics Engineer job openings:
Manager Data Analytics Engineer jobs near you
Infographic showing various Manager Data Analytics Engineer job openings in Minnesota as of June 2026, with employment types broken down into 94% Full Time, 2% Part Time, and 4% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution.
Manager, Data Engineering

Manager, Data Engineering

Post Consumer Brands

Lakeville, MN • On-site

Full-time

Posted 26 days ago

Post Consumer Brands rating

8.0

Company rating: 8.0 out of 10

Based on 17 frontline employees who took The Breakroom Quiz

74th of 389 rated food and drinks producers

Job description

Business Unit Overview
Headquartered in Lakeville, Minn., Post Consumer Brands, a business unit of Post Holdings, Inc., is dedicated to providing people and their pets with delicious food choices for every taste and budget. The company's portfolio includes beloved brands such as Honey Bunches of Oats™, PEBBLES™, Grape-Nuts™ and Malt-O-Meal™ cereal and Peter Pan™ peanut butter, as well as Rachael Ray® Nutrish™, Kibbles 'n Bits™ and 9Lives™ dog and cat food. Post also provides private label solutions to customers in pet food, cereal, nut butters and granola. As a company committed to high standards of quality and to our values, we are driven by one idea: To make lives better by making delicious food accessible for all. For more information about our brands, visit www.postconsumerbrands.com and follow us on LinkedIn or Facebook for the latest news.
Location Description
Post Consumer Brands corporate headquarters in Lakeville, Minnesota, is about 20 miles south of Minneapolis and St. Paul, Lakeville has all the benefits of smaller town living with access to everything a large metropolitan area has to offer. Join more than 400 team members collaborating on the two-building campus to help put breakfast on the tables of millions of consumers in North America.
Responsibilities
Manager, Data Engineering
Location: Hybrid in Lakeville, MN
About the Role
At Post Consumer Brands, data is a strategic asset and the Manager, Data Engineering plays a pivotal role in shaping how we turn data into insight, impact, and innovation. This role leads the design, development, and operation of our modern data engineering foundation, powering trusted analytics, self-service reporting, and AI-ready data products across the enterprise.
You'll lead a team of data engineers responsible for building high-quality, scalable data pipelines, data models, and semantic layers that support critical business decisions. Acting as both a people leader and technical leader, you'll balance delivery speed, reliability, and forward-looking modernization, while partnering closely with Analytics Solutions, Architecture, Governance, and business stakeholders.
This role reports to the Associate Director of Data & Analytics and serves as a key technical leader within our evolving, product-oriented data ecosystem.
Key Responsibilities
Data Engineering Foundation & Delivery
  • Lead the design, development, and maintenance of data pipelines, data models, semantic models, and data platforms aligned to enterprise standards
  • Deliver curated, durable, and reusable data assets aligned to priority business decision domains
  • Ensure timely, accurate, and reliable availability of data across enterprise analytics use cases

Technical Design & Scalability
  • Partner with Data & Analytics Architecture to align solutions with enterprise standards and best practices
  • Ensure platforms and pipelines are scalable, performant, maintainable, and adaptable
  • Make informed tradeoff decisions across performance, cost, and delivery speed

Modern Data Ecosystem Enablement
  • Build AI/ML-ready and product-oriented data engineering capabilities
  • Engineer low-latency and real-time data pipelines for operational analytics and intelligent applications
  • Develop ingestion and processing frameworks for structured and unstructured data

Data Trust, Reliability & Operational Readiness
  • Embed data quality, documentation, lineage, and observability into data assets
  • Ensure production-grade reliability and operational readiness in partnership with Governance and D&A Operations

Enablement of Analytics & Self-Service
  • Partner with Analytics Solutions to enable BI, advanced analytics, and data science
  • Deliver trusted, well-modeled semantic layers that empower self-service analytics

Team Leadership & Capability Development
  • Lead, mentor, and develop a team of on-shore data engineers and coordinate with off-shore partners
  • Foster a culture of engineering excellence, accountability, and continuous improvement
  • Drive adoption of modern tools, practices, and AI-enabled engineering workflows

Operational Excellence & Continuous Improvement
  • Translate enterprise priorities into executable delivery plans
  • Balance speed, quality, and sustainability across delivery and operations
  • Leverage automation and AI tools to improve efficiency and code quality

Qualifications
What We're Looking For
Required Qualifications
  • 5+ years of experience in data engineering, data warehousing, or related disciplines
  • 2+ years of experience leading data engineering teams and enterprise-scale platforms
  • Strong experience with modern cloud data stacks (e.g., Snowflake, dbt, ELT tools)
  • Proven expertise in data modeling, including dimensional and domain-oriented/semantic models
  • Experience building production-grade pipelines with testing, monitoring, and CI/CD
  • Familiarity with data quality, observability, and governance practices
  • Experience leveraging AI tools to accelerate engineering workflows
  • Strong collaboration, communication, and stakeholder-management skills
  • Bachelor's Degree REQUIRED in a technical or quantitative field (advanced degree preferred)

Preferred Qualifications
  • Experience in CPG, manufacturing, supply chain, or commercial analytics
  • Experience in federated or product-oriented data operating models
  • Exposure to real-time streaming, generative AI, LLM-enabled analytics, or RAG architectures
  • Working knowledge of metadata, lineage, access controls, and data governance concepts
  • Strong business acumen and comfort operating in ambiguity

Why You'll Love This Role
At Post Consumer Brands, you'll find big company opportunity with a small company attitude, the chance to work with iconic brands and enterprise-scale data, while still having the autonomy to make meaningful impact. You'll help shape a modern, AI-ready data foundation, lead and grow a talented engineering team, and directly influence how data drives smarter decisions across the business.
We value curiosity, ownership, and outcomes. You'll be trusted to build clarity, elevate standards, and move the organization forward, while being supported by a collaborative, growth-oriented culture that respects work-life balance and personal development.
Ready to Make an Impact?
If you're excited to lead, build, and modernize data engineering capabilities that power real business outcomes and you thrive in an environment where your ideas and leadership truly matter, we'd love to hear from you! Apply today and help shape the future of data at Post Consumer Brands.
The pay range for this position is $102,931 - $152,338 per year.

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