Engineering Manager

Ovative Group; Minneapolis (MN); On-site; USD 140,000 - 190,000; Full time

Job summary

Ovative Group in Minneapolis is seeking an Engineering Manager to lead the Data Products team. You will set the delivery rhythm, grow engineers across multiple disciplines, and represent data access and governance to a broad set of partners.

You will partner with Engineering Leads and Product Managers to deliver business-critical data and features. The right candidate earns credibility through disciplined delivery, strong judgment, and clear communication.

Qualifications

• 5+ years of software or data engineering management experience.
• Experience leading data products, pipelines, and governance.
• Familiarity with modern data platforms and orchestration tools.

Responsibilities

• Own the delivery plan for each sprint with Product Owner and Engineering Leads.
• Lead engineers across data engineering, full stack, and QA.
• Ensure code quality, security, and maintainability.
• Manage stakeholder relationships including client-delivery-related work.
• Foster psychological safety and responsible AI practices.

Skills

Data engineering leadership

Data governance

Cloud data platforms

Agile methodologies

Communication

Tools

Dagster

Databricks

dbt

Airflow

BigQuery

Snowflake

Job description

About Ovative Group

Ovative Group is an independent, full-funnel media, measurement, and creative firm transforming how brands grow. We partner with leading names like American Eagle, Best Buy, Domino's, The Home Depot, Polaris, and UnitedHealth Group to build smarter media and measurement programs that drive real, profitable growth.

We don't just track performance-we redefine it. Powered by our proprietary intelligence platform, EMRge, and our holistic metric Enterprise Marketing Return (EMR), we help brands connect revenue, customer, and brand outcomes into one clear picture of success. Our approach to full-funnel strategy, buying, and measurement delivers results that matter—and it's getting noticed. Our work has been recognized by Digiday, Google, USA Today, Inc. 5000, and Search Engine Land.

About the Role

Data Products owns the data and infrastructure that lets everyone at Ovative, and our clients, access data and reporting they need. The team builds on a modern stack, including Dagster, Databricks, and dbt, and is responsible for how data moves through the organization, from ingest, data modeling, and permissions that govern who can access it.

We're looking for an Engineering Manager to lead this team. You'll set the delivery rhythm, grow engineers across multiple disciplines, and represent Data Products to a broad set of partners who depend on the team for data access and governance. You'll partner closely with our Engineering Leads and Product Mangers to deliver business critical data and features for the organization. The right candidate earns real credibility with senior engineers through good judgment and consistent delivery.

Responsibilities of an Engineering Manager

Delivery & Planning

• Own the delivery plan for each sprint together with the Product Owner and our Engineering Leads, and make sure sprint backlogs are made up of clear, well-scoped stories the team can confidently deliver.


• Keep the team's delivery rhythm steady, and when scope needs to shift, work that through deliberately as part of planning.

People Leadership

• Hold regular 1:1s and give feedback that's specific enough to act on, across the team's disciplines, including data engineering, full stack, and QA.


• Set clear expectations for ownership and quality, and address issues as they come up.


• Build plans together with the team, and hold each other accountable for getting deliverables out the door.


• Create stretch opportunities that help people grow in ownership and versatility as the team matures, and recognize people for how they work as well as what they ship.

Engineering Quality & Practices

• Keep code reviews timely and focused on maintainability, stability, and security.


• Make sure code, especially AI-generated code, is fully understood and owned by whoever submits it.


• Build and manage team health reporting to ensure operations are strong and the team has what it needs to succeed.

Cross-Team & Stakeholder Management

• Manage relationships across a wide set of partners including operations teams, client delivery teams, and executive stakeholders that are critical inputs into our work.


• Partner with Product Owner to dial in requirements and priorities across business facing needs, engineering excellence, and overall efficiency.


• Advocate for the team's needs, keep expectations with stakeholders realistic, and communicate early enough that nothing comes as a surprise.

Culture & AI Adoption

• Foster psychological safety by modeling openness and treating mistakes as learning opportunities. Run honest retros and bring the team into hard decisions together.


• Champion responsible use of AI-assisted development tools, and help the team find patterns that speed up delivery while protecting quality and security.

Requirements

• 5+ years of experience in software or data engineering, or a related technical discipline, including direct management experience leading engineers (including senior or lead engineers).


• Working familiarity with modern data platform and orchestration tooling (e.g., Dagster, Airflow, or similar), cloud data warehousing (e.g., Databricks, BigQuery, Snowflake), and transformation frameworks (e.g., dbt), enough to manage and prioritize the work confidently.


• Strong technical literacy and comfort with data pipeline concepts.


• Demonstrated experience managing relationships across multiple stakeholder groups, including client-delivery-adjacent work such as access and governance requests.


• Experience with Agile methodologies in a sprint-based product delivery model.


• Strong written and verbal communication skills across technical and non-technical audiences.

Preferred

• Experience managing data governance or access-control processes (e.g., access controls, SOC2 compliance, CVE remediation).


• Experience with, or a strong demonstrable interest in, agentic AI technologies and setting practical guardrails for AI-assisted or AI-generated code.


• Experience with marketing APIs, ad-tech data, or automating data pulls from marketing platforms.