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Manager Data Engineering Jobs in Minnesota (NOW HIRING)

legence

Power BI Data Engineer

Minneapolis, MN · On-site +1

$119K - $143K/yr

... in data engineering with exceptional data visualization abilities. This hands-on role requires ... Implement and manage data warehouses and data lakes using Azure Synapse Analytics, SQL Server, or ...

Dlapiper

Data Engineer

Minneapolis, MN

$119K - $143K/yr

... data engineering practice) to deliver analytics-ready data. * Consolidate data from multiple sources into a centralized integration point (e.g., a single SQL Server instance) and manage field ...

legence

Power BI Data Engineer

Minneapolis, MN · On-site +1

$119K - $143K/yr

... in data engineering with exceptional data visualization abilities. This hands-on role requires ... Implement and manage data warehouses and data lakes using Azure Synapse Analytics, SQL Server, or ...

IP Corporation

Sr. Data Engineer

Saint Paul, MN · On-site

$115K - $145K/yr

Experience implementing enterprise security, lineage, metadata, and access management strategies. * Knowledge of real-time or streaming data architectures. * Microsoft Fabric, Azure Data Engineering ...

Kendall Howard

Data Engineer

Chisago City, MN · On-site

$80K - $120K/yr

Working closely with IoT Systems Engineering and Service teams, you'll help shape a new platform as ... Optimize database performance and manage schema migrations. Data Processing * Develop ETL/ELT ...

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Showing results 41-60

All JobsData Engineering JobsManager Data Engineering JobsManager Data Engineering Jobs in Minnesota

Manager Data Engineering information

See Minnesota salary details

$30.4K

$95.1K

$168.5K

How much do manager data engineering jobs pay per year?

As of Aug 16, 2026, the average yearly pay for manager data engineering in Minnesota is $95,145.00, according to ZipRecruiter salary data. Most workers in this role earn between $64,600.00 and $122,900.00 per year, depending on experience, location, and employer.

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

AspectManager Data EngineeringData Engineer
Required CredentialsBachelor's or Master's in CS, Data Science, or related; often leadership experienceBachelor's or higher in CS, IT, or related; technical certifications optional
Work EnvironmentTeam leadership, project management, strategic planningData pipeline development, coding, data modeling
Employer & Industry UsageTech companies, finance, healthcare, where data teams are commonData-focused roles across various industries

The main difference is that Manager Data Engineering oversees data teams and projects, focusing on strategy and leadership, while Data Engineers handle the technical implementation of data pipelines and infrastructure. Managers typically have more experience and leadership skills, whereas Data Engineers are more hands-on with coding and data architecture.

What are the key skills and qualifications needed to thrive as a manager data engineering?

To thrive as a Manager Data Engineering, you need expertise in data architecture, advanced analytics, and leadership, typically supported by a degree in computer science or a related field. Familiarity with big data tools (like Hadoop, Spark), data warehousing systems, cloud platforms (AWS, Azure), and certifications such as AWS Certified Data Analytics are highly valued. Strong communication, problem-solving, and team management skills help drive project success and foster collaboration. These skills ensure effective data solutions, alignment with business goals, and the ability to lead and grow high-performing engineering teams.

What are the roles and responsibilities of a manager data engineering?

A Manager Data Engineering oversees teams that design, build, and maintain data infrastructure and pipelines for organizations. They are responsible for ensuring the efficient flow and storage of data, implementing best practices in data management, and collaborating with stakeholders to meet business data needs. Additionally, they mentor and guide data engineers, manage project timelines, and ensure data security and quality standards are met. Their role often involves strategic planning to enable data-driven decision making across the company.

How does a manager data engineering typically collaborate with data scientists and business stakeholders?

A Manager of Data Engineering often serves as a bridge between technical teams and business stakeholders. They work closely with data scientists to ensure that data pipelines and infrastructure meet analytical needs, while also translating business requirements into actionable engineering solutions. Regular coordination meetings, clear documentation, and cross-functional projects are common, enabling seamless collaboration and alignment on goals. This role requires strong communication skills and the ability to balance technical priorities with business objectives.

What are the most commonly searched types of Data Engineering jobs in Minnesota?

The most popular types of Data Engineering jobs in Minnesota are:

What are popular job titles related to Manager Data Engineering jobs in Minnesota?

For Manager Data Engineering jobs in Minnesota, the most frequently searched job titles are:

What job categories do people searching Manager Data Engineering jobs in Minnesota look for?

The top searched job categories for Manager Data Engineering jobs in Minnesota are:

What cities in Minnesota are hiring for Manager Data Engineering jobs?

Cities in Minnesota with the most Manager Data Engineering job openings:

Manager Data Engineering jobs near you
Infographic showing various Manager Data Engineering job openings in Minnesota as of July 2026, with employment types broken down into 86% Full Time, 13% Part Time, and 1% Contract. Highlights an 82% Physical, 3% Hybrid, and 15% Remote job distribution, with an average salary of $95,145 per year, or $45.7 per hour.

Data Governance Lead

Inspire Medical Systems Inc.

Minneapolis, MN • On-site

Full-time

Posted 11 days ago

Job description

  • The Data Governance Lead will build and mature Inspire's enterprise data governance program, establishing the policies, processes, and stewardship practices that ensure data is trusted, governed, and fit for business and regulatory use.

    This role partners closely with business leaders, data owners, data stewards, data engineering and analytics teams to improve data quality, master data, and governance adoption across the organization. The Data Governance Lead will help embed governance principles into data products and engineering processes.

    We are looking for a collaborative, business-oriented data governance leader who can help scale governance practices and AI readiness across Inspire's modern data ecosystem while enabling trusted data products, regulatory readiness, and measurable business outcomes.

    Key Responsibilities

    • Build and mature Inspire's enterprise data governance program, operating model, and stewardship framework.
    • Establish and maintain governance standards, policies, and best practices for data ownership, quality, metadata, lineage, security, data products, and lifecycle management.
    • Partner with business stakeholders to establish data ownership, stewardship responsibilities, governance processes, and critical data elements that ensure accountability for enterprise data assets.
    • Partner with business leaders to define and align organizational KPIs and performance measures that improve visibility into strategic priorities, operational performance, and business outcomes.
    • Serve as the governance representative in technical discussions, providing leadership and guidance on data modeling, metadata, lineage, master data, data quality, and trusted data product design ensuring alignment with governance, quality, and stewardship standards.
    • Lead metadata management, data catalog, lineage, master data, and stewardship initiatives across the enterprise.
    • Facilitate governance councils, stewardship forums, and cross-functional working sessions.
    • Drive adoption of governance practices across business and technology teams through education, engagement, and measurable outcomes.
    • Promote the creation of trusted, well-documented, and reusable data products that support reporting, analytics, decision-making, and emerging AI capabilities.
    • Partner with business leaders, Quality, Privacy, Legal, Regulatory, and Information Security teams to ensure data governance practices support regulatory compliance while enabling business outcomes.
    • Measure and communicate governance program maturity, adoption, and business value.

    Required Qualifications

    • 5+ years of experience in data governance, data management, master data management, data quality, analytics, or a related discipline.
    • Experience building or maturing an enterprise data governance program.
    • Ability to engage effectively with architects, engineers, and analytics teams on topics including data modeling, data integration, data quality, metadata, lineage, master data management, and data product design.
    • Strong ability to influence and drive changes across business and technology organizations.
    • Excellent communication, facilitation, and stakeholder management skills.
    • Strong organizational, analytical, and problem-solving skills with the ability to manage competing priorities in a dynamic, results-oriented environment.
    • Commitment to continuous improvement, practical problem solving, and advancing data governance maturity across the organization.

    Preferred Qualifications

    • Experience with modern Microsoft and Azure data platforms, including Profisee, Purview, Databricks, and Unity Catalog.
    • Experience in a regulated industry such as medical devices, healthcare, life sciences, or other compliance-focused environments.
    • Experience partnering with data engineering and analytics teams to operationalize governance practices.
    • Familiarity with data cataloging, Lakehouse architecture, Medallion architecture, and trusted data products.
    • Experience serving as a business, governance, or product lead for enterprise data platforms and governance technologies.
    • Experience coordinating work with offshore, contractor, or managed services resources.
    • Experience presenting data concepts, risks, metrics, and recommendations to executive stakeholders.
     

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