Data & AI Product Owner - ITS

Mortenson is currently seeking a Data & AI Product Owner that serves as the voice of the customer and business for Mortenson’s governed data products and AI solutions-ensuring each capability delivers measurable value, is trusted, and aligns with enterprise priorities. This role bridges strategy and execution by owning roadmaps and backlogs across the data-to-AI lifecycle: domain data products in the governed data mesh (Microsoft Fabric) and the AI experiences built on top of them. The Product Owner also owns the Agile delivery process across Data & AI teams (including Scrum Master duties) to enable predictable, transparent execution and continuous improvement. The Product Owner partners with Operating Groups (OGs) and Business Services Groups (BSGs) to identify high-impact opportunities, define outcomes, and drive adoption-supporting Mortenson’s 2026 priorities for AI readiness, scalable data products, responsible AI delivery, and innovation enablement., Product Vision & Roadmap (Data + AI)

• Define and communicate the vision, goals, and success metrics for data products and AI products in alignment with Mortenson’s Data & AI strategy.
• Maintain and prioritize the product backlog(s), ensuring clarity, sequencing, and alignment with business objectives and technical dependencies.
• Translate business needs into actionable epics/user stories, data requirements, and acceptance criteria (including non-functional needs such as performance, security, and auditability).

Agile Process Ownership (Data + AI) - including Scrum Master duties

• Own and continuously improve the Agile operating cadence across Data & AI product delivery teams (single-team or multi-team), ensuring visibility, flow, and predictable outcomes.
• Facilitate core Scrum/Agile ceremonies as needed: sprint planning, daily stand-ups, backlog refinement, sprint review/demo, and retrospectives.
• Partner with Engineering and stakeholders to ensure sprint goals are clear, work is right-sized, dependencies are managed, and Definition of Ready/Done is consistently applied.
• Identify, track, and remove impediments; escalate risks and blockers early with options and recommended paths forward.
• Monitor team health and delivery signals (cycle time, throughput, WIP, spillover) and drive continuous improvement actions.

• Coordinate cross-team dependencies and release readiness across data engineering, analytics engineering, data science, and MLOps/LLMOps. Data Product Ownership (Governed Data Mesh / Microsoft Fabric)

• Partner with domain teams to define and evolve data products (e.g., curated datasets, metrics, semantic models) with clear ownership, documentation, and consumer-focused design.
• Establish and monitor data quality expectations (definitions, SLAs, validation rules), and drive remediation for defects and root causes.
• Ensure data products meet governance standards: lineage, access controls, privacy classification, retention, and appropriate use.

• Enable self-service analytics and AI by improving discoverability, interoperability, and standardization across domains. AI Product Ownership (Use Cases, Experience, and Value Delivery)

• Partner with OG/BSG leaders to identify high-value AI use cases and define measurable outcomes (efficiency, risk reduction, revenue impact, safety, quality).
• Serve as the primary liaison between business stakeholders and AI delivery teams, ensuring transparency, prioritization discipline, and timely decision-making.

• Drive adoption through demos, enablement, training, and change management initiatives; incorporate user feedback into iterative releases. Governance, Risk & Responsible AI

• Ensure features meet Mortenson’s AI governance standards (privacy, security, ethical use, model risk) and coordinate reviews/approvals as needed.

• Collaborate with the AI COE to embed responsible AI practices into the product lifecycle (data minimization, bias testing, human-in-the-loop, monitoring). Delivery & Continuous Improvement

• Work closely with Data Engineers, Analytics Engineers, Data Scientists, AI Engineers, and MLOps teams to ensure timely delivery and quality outcomes.
• Monitor product performance post-launch; iterate based on feedback, telemetry, and business impact measurement.
• Champion innovation by introducing emerging data and AI capabilities that align with Mortenson’s roadmap and can be delivered safely at scale., As a top builder, developer, and EPC (Engineering, Procurement, and Construction), our expertise spans markets like sports, renewable energy, data centers, healthcare, and more. We are builders at heart, working to ensure the built environment has a lasting positive impact., Other Items to Note
• Mortenson reserves the right to hire any individual without legal or financial obligation on unwanted solicitations. No agency emails, calls, or solicitations are accepted without a valid agreement.
• Must be currently legally authorized to work in the U.S. without sponsorship for employment visa status (e.g., H1B status, 0-1, TN, CPT, OPT, etc.). We are unable to sponsor or take over sponsorship of an employment Visa at this time.

• Bachelor’s degree in Computer Science, Information Systems, Data Analytics, Business, or related field (or equivalent experience).
• 5+ years in product ownership/management for data, analytics, AI/ML, or other digital products.
• Demonstrated experience defining outcomes, prioritizing backlogs, and translating business needs into deliverable requirements and acceptance criteria.
• Demonstrated experience owning Agile delivery processes (Scrum/Kanban), facilitating ceremonies, removing impediments, and driving continuous improvement (Scrum Master responsibilities).
• Working knowledge of governed data concepts (data quality, metadata, lineage, access controls) and how they enable analytics and AI at scale.
• Strong understanding of Agile frameworks and backlog management tools; excellent stakeholder facilitation and communication skills.

Preferred:

• Scrum Master and/or Agile certification (CSM, PSM, SAFe, PMI-ACP) or equivalent practical experience.
• Experience in enterprise data platforms and patterns (e.g., Microsoft Fabric, lakehouse, semantic models) and/or data mesh/data product operating models.
• Experience with MLOps/LLMOps practices and AI governance frameworks (monitoring, drift, model risk management).
• Experience in AEC/construction technology or enterprise-scale operational systems.
• Background in responsible/ethical AI, privacy, and security compliance.

• Medical and prescription drug plans that includes no additional cost vision coverage
• Dental plan
• 401k retirement plan with a generous Mortenson match
• Paid time off, holidays, and other paid leaves
• Employer paid Life, AD&D, and disability insurance
• No-Cost mental health tool and concierge with extensive work-life resources
• Tuition reimbursement
• Adoption Assistance
• Gym Membership Discount Program

The base pay range for this role is $107,300 - $161,000. (Actual range is higher for the following office locations: Denver, CO and Chicago, IL - 5%, Seattle, WA, and Portland, OR - 10%, Washington, D.C. - 12.5%). This position is eligible for Mortenson’s incentive plan.

Base pay is positioned within the range based on several factors including an individual’s knowledge, skills, and experience, with consideration given to internal equity.