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Martech Data Engineer Jobs in Minnesota (NOW HIRING)

Director, Product (Minneapolis)

Minneapolis, MN · On-site

$243K - $254K/yr

You will work directly with Product, Data Engineering, Client Services, and Commercial teams to ... martech, or data-driven environments. * Demonstrated experience defining and scaling products ...

Director, Product

Minneapolis, MN · On-site

$130 - $180/hr

You will work directly with Product, Data Engineering, Client Services, and Commercial teams to ... martech, or data-driven environments. * Demonstrated experience defining and scaling products ...

Engineering Manager

Minneapolis, MN · On-site

$90 - $132/hr

Our proprietary MarTech platform, EMRge, turns marketing into a driver of sustainable growth by ... data solutions that enhance performance, stability, and scalability. You will guide the team ...

Design Director, Platform UI

Minneapolis, MN · On-site

$161K - $198K/yr

... engineering. * Deep experience designing for enterprise platforms, B2B SaaS, MarTech, content and ... If you would like more information about how your data is processed, please contact us. apply for ...

... engineering. * Deep experience designing for enterprise platforms, B2B SaaS, MarTech, content and ... If you would like more information about how your data is processed, please contact us.

GTM Architect

Eden Prairie, MN · On-site

$146K - $191K/yr

... data initiatives. * Mentorship : Mentor developers, offering direct guidance on technical issues ... Stay current with MarTech, SalesTech, and AI automation trends, sharing best practices with the ...

GTM Architect

Eden Prairie, MN · On-site

$146K - $191K/yr

... data initiatives. * Mentorship : Mentor developers, offering direct guidance on technical issues ... Stay current with MarTech, SalesTech, and AI automation trends, sharing best practices with the ...

Showing results 21-40

Martech Data Engineer information

What is a Martech Data Engineer?

A Martech Data Engineer is a technology professional who specializes in building and maintaining the data infrastructure that supports marketing technology (Martech) platforms. They enable the collection, integration, and analysis of marketing data from multiple sources, ensuring data quality and accessibility for marketing teams. Their work helps organizations make data-driven marketing decisions, personalize customer experiences, and measure campaign effectiveness. Martech Data Engineers often collaborate with marketers, analysts, and other engineers to implement data pipelines and optimize marketing operations.

How does a Martech Data Engineer typically collaborate with marketing and analytics teams to achieve business goals?

As a Martech Data Engineer, you will regularly partner with marketing and analytics teams to design, build, and maintain data pipelines that support campaign performance tracking and customer segmentation. You’ll work closely with marketers to understand their data needs and translate them into scalable technical solutions, often attending cross-functional meetings to plan new data integrations or troubleshoot issues. Collaboration also involves ensuring data quality, managing ETL processes, and enabling self-serve analytics by making data accessible and reliable for non-technical stakeholders. This close teamwork helps drive data-driven decision-making and ensures marketing strategies are effectively measured and optimized.

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

To thrive as a Martech Data Engineer, you need a solid background in data engineering, SQL, and marketing technology platforms, typically supported by a degree in computer science or a related field. Familiarity with ETL tools, cloud data platforms (such as AWS or GCP), and certifications in marketing automation systems like Salesforce or Adobe Experience Cloud are highly valuable. Strong problem-solving abilities, attention to detail, and effective communication skills help bridge the gap between marketing and technical teams. These skills enable the efficient integration, analysis, and utilization of marketing data, driving better decision-making and campaign performance.

What is the difference between Martech Data Engineer vs Data Analyst?

AspectMartech Data EngineerData Analyst
Required CredentialsBachelor's in Computer Science, Data Engineering certificationsBachelor's in Statistics, Data Analysis certifications
Work EnvironmentData pipelines, cloud platforms, marketing tech toolsData visualization, reporting, business insights
Employer & Industry UsageMarketing agencies, tech companies, e-commerceMarketing teams, business intelligence units
Common Search & Comparison IntentUnderstanding technical data roles in marketingAnalyzing marketing data for insights

The Martech Data Engineer focuses on building and maintaining data pipelines and infrastructure for marketing data, while the Data Analyst interprets data to generate insights and reports. Both roles are essential in marketing tech environments but serve different functions within data management and analysis.

What are popular job titles related to Martech Data Engineer jobs in Minnesota?

For Martech Data Engineer jobs in Minnesota, the most frequently searched job titles are:

What job categories do people searching Martech Data Engineer jobs in Minnesota look for?

The top searched job categories for Martech Data Engineer jobs in Minnesota are:

What cities in Minnesota are hiring for Martech Data Engineer jobs?

Cities in Minnesota with the most Martech Data Engineer job openings:

Infographic showing various Martech Data Engineer job openings in Minnesota as of August 2026, with employment types broken down into 1% As Needed, 82% Full Time, 11% Part Time, and 6% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution.

Director, Product (Minneapolis)

Medium

Minneapolis, MN • On-site

$243K - $254K/yr

Full-time

Re-posted 18 days ago


Job description

Join a National Top Workplace

Named a Top Workplace in the USA and Top Remote Workplace, Kobie is where the best minds in loyalty come together, driven by passion and innovation. We’re always looking for talented individuals who are ready to join a collaborative, growth-focused culture. As a partner to some of the world’s most recognized brands, we are leaders in loyalty, helping brands build lasting emotional connections with their consumers.

Join Us from Anywhere

While our headquarters are nestled in sunny St. Petersburg, Florida, Kobie embraces a flexible work environment, offering teammates the freedom to work remotely. We understand the importance of work-life balance and support our team with:

  • Flexible Time Off to recharge when needed
  • Nine Company-Wide Holidays
  • A diverse suite of benefits prioritizing your growth, development, and personal well-being

Discover more about our perks and benefits here.

Kobie's Product Management organization is evolving from project execution to a P&L ownership model — where leaders drive revenue, customer satisfaction, and the commercial value of Kobie's data capabilities. This role sits at the center of that transformation.

As Director, Product you will define what Kobie's data platform means as a market-facing product: how behavioral and transactional data becomes the engine behind smarter loyalty programs, better marketing performance, and more personalized customer experiences. You will set strategy for KLICs and the Data Engine, build the commercial model to monetize them, and ensure our data capabilities fuel AI-driven outcomes — not just move data between systems. Success at year one looks like increased attach rates, at least one AI-powered capability live with measurable client outcomes, and clear differentiated positioning of Kobie's data platform in the market.

You will work directly with Product, Data Engineering, Client Services, and Commercial teams to convert Kobie's data assets into scalable, repeatable offerings.

How you will make an impact Data product strategy & outcomes orientation
  • Define Kobie's data product portfolio with a clear focus on marketing, loyalty, and customer experience outcomes — establishing product boundaries, value propositions, and positioning for KLICs and the Data Engine that go well beyond data movement or pipeline delivery.
  • Set the standard for what AI-ready data means at Kobie — ensuring our behavioral and transactional data is structured, governed, and accessible in ways that support real-time personalization, predictive modeling, and AI-assisted marketing workflows.
  • Drive the long-term roadmap for data capabilities that help clients transform unified customer data into actionable audiences, personalized experiences, and measurable loyalty outcomes.
AI-enabled product evolution
  • Embed practical AI-driven capabilities into existing data products — identifying where AI should assist, accelerate, or automate across the loyalty and marketing analytics lifecycle, in ways that are durable and commercially scalable.
  • Partner with Data Engineering and Data Science to ensure AI and ML outputs — propensity models, segment recommendations, next-best-action signals — are productized as client-facing capabilities with clear value propositions, not internal experiments.
  • Actively use AI in your own product workflow; bring firsthand fluency to decisions about where AI belongs in a product and where it doesn't.
Commercialization, pricing & packaging
  • Own pricing and packaging strategies for data-driven offerings — usage-based, tiered, and outcome-based models; define the unit of value and validate willingness-to-pay with commercial teams.
  • Improve attach rates and revenue contribution of data products by translating platform capabilities into client-facing value narratives that sales and client services can execute against.
  • Own the commercialization framework for new AI-enabled capabilities — from proof-of-concept through pricing validation, GTM readiness, and first client deployment.
Productization of client solutions
  • Partner with Client Services to identify repeatable patterns across bespoke client work and convert them into standardized, scalable product offerings — with a clear framework for what gets productized versus what stays custom.
  • Build structured intake and prioritization for product signals from Client Services, Business Development, and clients — roadmap direction driven by patterns and commercial opportunity, not reactive one-off requests.

What you need to be successful

Required
  • 8–12+ years of product management experience owning commercial outcomes for data, platform, analytics, or engagement products in technology, martech, or data-driven environments.
  • Demonstrated experience defining and scaling products focused on marketing, loyalty, or customer experience outcomes — not just data infrastructure delivery or database-to-database movement.
  • Actively uses AI in their own product workflow; can articulate where AI should assist, accelerate, or automate — and may have vibe-coded their own solutions.
  • Strong commercial acumen: pricing, packaging, and monetization strategy; hands‑on experience with usage-based, tiered, or outcome-based pricing models; has owned the unit‑of‑value definition for a product.
  • Proven ability to influence across complex, cross‑functional environments without always having direct authority — drives a sharp point of view from concept through build and first sale.
  • Analytical mindset with the ability to translate behavioral data, model outputs, and client feedback into strategic product decisions.
Strongly preferred
  • Experience with behavioral data platforms, customer data infrastructure, or CDPs — how event-level data is collected, governed, and activated for personalization and AI use cases.
  • Familiarity with loyalty program data economics — how transactional, behavioral, and engagement signals combine to drive member retention, offer optimization, and lifetime value.
  • Experience integrating AI and ML capabilities — propensity models, recommendation engines, next‑best‑action — into existing product workflows rather than shipping standalone AI features.
  • Background in or exposure to agentic AI workflows, real-time decisioning, or AI‑assisted campaign and offer optimization.
  • Experience in adjacent domains — retail media, fintech data products, adtech, or digital analytics — where data monetization and client‑outcome orientation are core to the product model.

This role is not a fit if

  • Your product experience is primarily in data engineering or infrastructure delivery — commercial ownership and client outcome orientation are central to this role.
  • AI is a talking point on your resume rather than something you actively use and build with today.
  • You've managed data platform roadmaps but have never owned pricing, packaging, or attach rate for a product.
  • You're most comfortable working within engineering — this role requires sustained fluency with commercial, client services, and executive audiences.

Employment at Kobie is based solely on an individual's merit and qualifications, which are directly related to professional competence. We do not discriminate against any teammate or applicant because of race, color, religion, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy, or any other characteristic protected by applicable law.

We are fiercely committed to fostering a workplace where teammates can bring their authentic selves to work every day. Our DEI initiatives, including various committees, ensure that principles of equity, diversity, and inclusion are deeply ingrained throughout Kobie. While our leadership team fully supports our policy of nondiscrimination and equal opportunity, it is the responsibility of all teammates to uphold these values.

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