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Manager Data Engineering Jobs in Wisconsin (NOW HIRING)

$211K - $246K/yr

Lead, mentor, and grow a team of data and analytics engineers. This includes hiring, performance management, career development, planning, and setting technical standards. * Technical Leadership:

The IT Manager, Data & Analytics owns and governs Komatsu's enterprise data and analytics platforms, including Palantir Foundry, Microsoft Power BI, Azure Synapse, and associated data engineering ...

Quanex is looking for a Manager, Data Governance to join our team located in Akron, OH, Owatonna ... This role partners closely with Engineering, IT, Manufacturing, Finance, and Operations ...

The Director, Data Engineering - Architect is responsible for defining and governing the enterprise ... Metadata management and lineage systems Ensure architectural consistency across environments ...

Industry/Sector Not Applicable Specialism Data, Analytics & AI Management Level Manager & Summary ... In data engineering at PwC, you will focus on designing and building data infrastructure and ...

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Data & Integration Manager

Brookfield, WI · On-site

$150K - $175K/yr

Change Management & Learning Agility Experience & Qualifications: * 8+ years of progressive experience in data engineering, integration, analytics, application development, business intelligence, or ...

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Manager Data Engineering information

See Wisconsin salary details

$31.3K

$98.1K

$173.6K

How much do manager data engineering jobs pay per year?

As of Jul 16, 2026, the average yearly pay for manager data engineering in Wisconsin is $98,053.00, according to ZipRecruiter salary data. Most workers in this role earn between $66,600.00 and $126,700.00 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, and why are they important?

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 Manager Data Engineering roles and responsibilities?

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 of 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 Wisconsin? The most popular types of Data Engineering jobs in Wisconsin are:
What are popular job titles related to Manager Data Engineering jobs in Wisconsin? For Manager Data Engineering jobs in Wisconsin, the most frequently searched job titles are:
What job categories do people searching Manager Data Engineering jobs in Wisconsin look for? The top searched job categories for Manager Data Engineering jobs in Wisconsin are:
What cities in Wisconsin are hiring for Manager Data Engineering jobs? Cities in Wisconsin with the most Manager Data Engineering job openings:
Sr. Manager, Data Engineering & Analytics

Sr. Manager, Data Engineering & Analytics

Serve Robotics

On-site, Remote

$211K - $246K/yr

Full-time

Posted 28 days ago


Job description

At Serve Robotics, we're reimagining how things move in cities. Our personable sidewalk robot is our vision for the future. It's designed to take deliveries away from congested streets, make deliveries available to more people, and benefit local businesses.
The Serve fleet has been delighting merchants, customers, and pedestrians along the way in Los Angeles, Miami, Dallas, Atlanta and Chicago while doing commercial deliveries. We're looking for talented individuals who will grow robotic deliveries from surprising novelty to efficient ubiquity.
Who We Are
We are tech industry veterans in software, hardware, and design who are pooling our skills to build the future we want to live in. We are solving real-world problems leveraging robotics, machine learning and computer vision, among other disciplines, with a mindful eye towards the end-to-end user experience. Our team is agile, diverse, and driven. We believe that the best way to solve complicated dynamic problems is collaboratively and respectfully.
Responsibilities
  • Lead the Team: Lead, mentor, and grow a team of data and analytics engineers. This includes hiring, performance management, career development, planning, and setting technical standards.
  • Technical Leadership: Define the data engineering and analytics roadmap, aligned with company goals. This includes prioritizing data platform investments, reporting needs, analytics capabilities, and cross-functional data initiatives.
  • Data Platform Ownership: Oversee the design, reliability, scalability, and governance of the company's data infrastructure, such as data warehouses, data lakes, ETL/ELT pipelines, orchestration systems, semantic layers, and BI tooling.
  • Analytics Delivery: Ensure business stakeholders have accurate dashboards, metrics, reporting, and ad hoc analysis to support decision-making across functions such as product, operations, finance, sales, marketing, and executive leadership.
  • Empowering Self-Service: Make self-service an organization-wide goal by building rich, trusted datasets and enabling access through AI-powered natural language interfaces.
  • Data Quality and Governance: Establish standards for data accuracy, lineage, documentation, access controls, privacy, security, and compliance.

Qualifications
  • 6+ years of professional experience in data engineering and analytics including 2+ years experience leading teams of Sr. Data/Analytics Engineers.
  • Data leadership experience: Proven experience managing data engineering, analytics engineering, BI, or analytics teams, including hiring, coaching, performance management, and roadmap planning.
  • Strong technical foundation: Deep understanding of data warehouses, data lakes, ETL/ELT pipelines, orchestration, data modeling, BI platforms, semantic layers, and data quality practices.
  • Experience with modern data stacks: Hands-on experience with tools such as Snowflake, BigQuery, Redshift, Databricks, dbt, Airflow, Fivetran, Looker, Tableau, Power BI, or similar platforms.
  • Cross-functional, business-oriented partnership: Strong track record partnering with executives and teams across product, operations, finance, engineering, sales and marketing, translating business goals into data strategy, dashboards and analytics products that improve decision-making.
  • AI-powered self-service analytics experience: Demonstrated ability to build trusted, governed data products and enable organization-wide access through natural language or AI-powered analytics interfaces, with strong controls for accuracy, security, privacy, compliance and usability.
  • Data governance expertise: Experience establishing standards for data quality, documentation, access controls, privacy, security, auditability, metric definitions, and trusted data products, including SOX, SOC2 compliance and compliance with international data policies and regulations (e.g., GDPR, data residency requirements).
  • Education or equivalent experience: Bachelor's degree in computer science, data science, engineering, statistics, mathematics, information systems, or a related field. Advanced degrees are a plus.

*Please note: The listed base salary range applies to candidates based in the US. Compensation may vary depending on location, experience, and role alignment. We are open to qualified candidates working remotely in Canada
  • Canada - ALL: $179,976 - CAD- $221,828 CAD