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Lead Data Engineer Jobs in Minnesota (NOW HIRING)

Senior Data Engineer

Minneapolis, MN · On-site

$110K - $150K/yr

Lead media data engineering initiatives Build and maintain integrations across major advertising, analytics, and marketing technology platforms. Develop scalable frameworks for campaign performance ...

Data Scientist

Virginia, MN · On-site

$95 - $130/hr

... engineering practices. Responsibilities * Lead Data Science Initiatives: Dive deep into complex and often nebulous requirements, applying expertise in areas such as time series forecasting and ...

New

Senior Data Engineer

Minnetonka, MN · On-site +1

$108K - $146K/yr

Build and optimize data processing frameworks on cloud platforms such as Databricks or Snowflake ... Lead technical design sessions and code reviews, promoting engineering best practices, reusability ...

Data Strategy-Manager

Minneapolis, MN · On-site

$99K - $232K/yr

You are expected to lead with integrity and authenticity, articulating our purpose and values in a ... Data Engineer / Azure Solutions Architect - Google Professional Data Engineer - DAMA CDMP ...

Lead data quality initiatives, including definition of metrics, ongoing monitoring, root-cause analysis, and remediation * Partner with Engineering and Manufacturing teams to align data structures ...

Lead data quality initiatives, including definition of metrics, ongoing monitoring, root-cause analysis, and remediation * Partner with Engineering and Manufacturing teams to align data structures ...

Showing results 41-60

Lead Data Engineer information

See Minnesota salary details

$41.6K

$121.2K

$176.8K

How much do lead data engineer jobs pay per year?

As of Aug 8, 2026, the average yearly pay for lead data engineer in Minnesota is $121,236.00, according to ZipRecruiter salary data. Most workers in this role earn between $100,400.00 and $132,200.00 per year, depending on experience, location, and employer.

How does a lead data engineer typically collaborate with data scientists and other engineering teams?

As a Lead Data Engineer, you play a central role in bridging the gap between raw data and actionable insights. You’ll collaborate closely with data scientists to understand their requirements, ensuring data pipelines deliver clean, reliable datasets for modeling and analysis. Additionally, you’ll work with software engineers and DevOps teams to integrate data solutions into production systems, maintain data infrastructure, and uphold best practices for data governance and security. Effective communication and cross-functional teamwork are key aspects of this role.

What are the key skills and qualifications needed to thrive as a lead data engineer?

To thrive as a Lead Data Engineer, you need advanced expertise in data architecture, database design, and programming languages like Python or Scala, typically supported by a degree in computer science or a related field. Familiarity with big data technologies (e.g., Hadoop, Spark), cloud platforms (AWS, Azure, GCP), and relevant certifications such as Google Professional Data Engineer are highly valued. Strong leadership, problem-solving abilities, and effective communication help drive team performance and translate business needs into technical solutions. These skills ensure robust, scalable data pipelines and successful collaboration across technical and business stakeholders.

What is the difference between Lead Data Engineer vs Data Engineer?

AspectLead Data EngineerData Engineer
CredentialsBachelor's/Master's in CS, Data Science, or related; often certifications in cloud platforms or data toolsBachelor's in CS, Data Science, or related; similar certifications
Work EnvironmentLeads data projects, mentors teams, designs architectureBuilds data pipelines, maintains databases, implements data solutions
Industry UsageUsed in organizations with complex data needs, overseeing data teamsCommon in companies handling large-scale data processing

The main difference is that Lead Data Engineers oversee data projects and teams, focusing on architecture and strategy, while Data Engineers focus on building and maintaining data pipelines. Both roles require similar skills and certifications, but the Lead Data Engineer has additional leadership responsibilities.

What is a lead data engineer?

Lead Data Engineers are senior professionals responsible for designing, building, and managing large-scale data systems and architectures within an organization. They oversee data engineering teams, set technical standards, and ensure efficient data flow and storage. Their role involves collaborating with data scientists, analysts, and other stakeholders to deliver reliable data solutions that support business goals. Lead Data Engineers also mentor junior engineers and help define best practices and strategies for data management.
What are popular job titles related to Lead Data Engineer jobs in Minnesota? For Lead Data Engineer jobs in Minnesota, the most frequently searched job titles are:
What job categories do people searching Lead Data Engineer jobs in Minnesota look for? The top searched job categories for Lead Data Engineer jobs in Minnesota are:
Infographic showing various Lead Data Engineer job openings in Minnesota as of August 2026, with employment types broken down into 100% Contract. Highlights an 100% In-person job distribution, with an average salary of $121,236 per year, or $58.3 per hour.

Senior Data Engineer

Omnicom

Minneapolis, MN • On-site

$110K - $150K/yr

Full-time

Posted 28 days ago


Job description

Agency:
Carmichael Lynch
Job Function:
Data and Analytics
Job Subfunction:
Data Science and Analytics
Job Description:
Summary of Job:
As a senior analytics engineer, you'll work across a dynamic client roster designing and building data solutions that connect media, site, and marketing performance data into actionable insights. You will partner closely with analytics, strategy, media, and client teams to architect scalable data solutions that answer business questions and support marketing decision-making.
This role requires a hands-on, solution-oriented engineer who combines deep technical expertise with a strong understanding of media and digital analytics. The ideal candidate proactively identifies opportunities, solves complex data challenges, and helps shape how data is leveraged across the agency and for our clients.
What You'll Do:
Design data solutions that solve client business needs
Partner with analytics and media teams to understand business objectives and translate them into scalable data solutions.
Design data models that integrate media, site, sales, and media conversion data to provide a complete view of marketing performance.
Recommend and implement measurement approaches that support both agency and client objectives.
Serve as a subject matter expert on media and marketing data architecture.
Lead media data engineering initiatives
Build and maintain integrations across major advertising, analytics, and marketing technology platforms.
Develop scalable frameworks for campaign performance measurement, attribution, audience analysis, and optimization.
Evaluate emerging platforms, APIs, and data sources to improve agency capabilities and client outcomes.
Build and maintain data pipelines
Automate reporting pipelines with speed, accuracy, and scalability in mind.
Demonstrate best practices in data engineering and account for considerations specific to media and site data in every step of the automation process.
Write and optimize SQL views, Python/R scripts, and API connectors as needed.
Continually optimize data cleaning and anomaly detection processes.
Help manage and advance our GCP infrastructure, particularly with BigQuery and GCP integrations.
Own data quality and governance
Enforce naming conventions, dataset groupings, versioning, and access standards.
Maintain rigorous QA practices to ensure clean, reliable, and consistent data.
Continuously seek opportunities to improve processes and infrastructure.
Solve problems relentlessly
Proactively catch and investigate issues, find root causes, and go beyond surface solutions.
Work with analysts to anticipate needs and ensure data is easy to find and use.
Demonstrate situational awareness and know when to escalate, push or pull back, or execute.
Communicate effectively with less technical stakeholders to address challenges and keep them updated on progress.
You Could Be a Good Fit If:
You take ownership of data quality and availability like it's mission critical.
You already are, or have the drive to become, an expert in media data.
You're a problem-solver who doesn't stop at "it's broken." You figure out why and how to fix it.
You balance speed and accuracy, knowing both matter in a client-driven environment.
You're adaptable, resourceful, and curious. You're able to figure things out with limited direction. Learning new things and finding creative solutions are some of your favorite parts of your job.
Requirements
Education:
A bachelor's degree preferred or equivalent work experience in related field such as computer science, data science, mathematics/statistics, marketing analytics, etc.
Skills and Experience:
6+ years of experience in data engineering, marketing analytics, media analytics, or related disciplines. Agency experience strongly preferred.
Expert-level SQL and Python skills with experience developing scalable production-grade data pipelines.
Deep experience working with digital media data, including campaign delivery, audience, conversion, and attribution datasets.
Proven experience designing and implementing data solutions that support media planning, optimization, measurement, and reporting.
Strong understanding of digital marketing ecosystems, including platforms such as Google Ads, CM360, DV360, The Trade Desk, Meta, LinkedIn, Adobe Analytics, and Google Analytics 4.
Experience integrating multiple data sources, including media, site analytics, offline conversion, and first-party customer data.
Deep experience with BigQuery, GCP, or similar cloud-based data warehouse environments.
Experience evaluating client business requirements and translating them into scalable technical solutions.
Experience building data products, automated reporting frameworks, and measurement solutions for internal and external stakeholders.
Experience with dashboarding and visualization tools such as Tableau, Looker, Power BI, or similar.
Competencies (Characteristics and Work Style):
Understands both the technical and business implications of data solutions.
Recommends approaches rather than simply execute requirements.
Builds credibility with clients and internal stakeholders through expertise and thoughtful problem solving.
Demonstrates ownership, initiative, and accountability from project inception through delivery.
Influences decisions and challenges assumptions when a better solution exists.
The salary range for this position is listed below. Where an employee or prospective employee is paid within this range will depend on a variety of factors, including but not limited to budget, relevant experience, qualifications, and tenure in similar roles. Consideration may also be given to internal salary data for current or former employees in the same or similar positions.
Salary Range: $105,000 - 135,000 annually$105,000.00 - $135,000.00
Omnicom's policy requires employees to work in the office for a minimum of three days a week, unless additional in-office days are directed by their agency or manager. Our objective is to increase this requirement over time, and many of our agencies as well as Omnicom's corporate group already require five days of in-office attendance.
Omnicom is committed to hiring and developing exceptional talent. We agree that talent is uniquely distributed, and we're focused on developing inclusive teams that can bring the best solutions to everything we do. We strongly believe that celebrating what makes us different makes us better together. Join us-we look forward to getting to know you. We will process your personal data in accordance with our Recruitment Privacy Notice.
Link to Recruitment Privacy Notice: https://www.omc.com/privacy-notice
For US Job Seekers:
It is the policy of Omnicom and any of its affiliates to provide equal employment opportunities to all employees and applicants for employment without regard to race, religion, color, ethnic origin, gender, gender identity, age, marital status, veteran status, sexual orientation, disability, or any other basis prohibited by applicable federal, state, or local law. EOE/AA/M/D/V/F.