Data Solutions Engineering Manager, Infrastructure Engineers

Data Solutions Engineering Manager, Kiewit Infrastructure Engineers

Location:

Lone Tree, CO, US Denver, CO, US

Requisition :178988

Job Level:Mid Level

Home District/Group:Kiewit Infrastructure Engineers

Department:Data Services

Market:Transportation

Employment Type:Full Time

In this role, you will lead a team of data analysts and solution engineers, acting as a central coordinator and problem-solver, interfacing between various data and technology groups to ensure smooth data operations and project delivery. You’ll work closely with the Kiewit Technology Group (KTG), Kiewit Data Services (KDS), and other internal teams within the district to identify and resolve data issues, guide analysts, and develop tools that improve our workflows.

You will be responsible to Manage and maintain historical project data to enable informed decision-making across the organization. This includes curating and organizing past project records to identify potential risks, improve job estimation accuracy, and establish connections between previous deliverables and new project requests. The role requires ensuring data integrity, accessibility, and relevance so that historical insights can be leveraged to optimize planning, mitigate challenges, and enhance overall project execution.

Kiewit Infrastructure Engineering (KIE) seamlessly transitions solutions from design to construction through the collaborative efforts of Design Engineering, Design Management, Proposals, Estimating, and Integrated Project Controls. Our construction-focused engineering approach involves a multidisciplinary team working together to maximize value for clients by improving schedules, controlling costs, and minimizing risk on infrastructure projects. This integrated strategy emphasizes collaboration and constructability throughout the project lifecycle, enabling us to identify and implement quality solutions with a strong safety focus.

Clients benefit from Kiewit’s proven processes and tools, which minimize project risk. As an in-house resource, we support projects across the company, in all major markets, sharing experiences, innovative concepts, and best practices. Kiewit’s management and implementation of this process result in safe, cost-effective, and innovative designs that exceed client expectations and uphold Kiewit’s legacy of excellence.

At Kiewit, we believe in building more than just structures – we build relationships, strengthen communities, and expand workforce capacity. We don't just build projects; we build careers. With top-notch health benefits, a wealth-building 401k plan (RRSP), and unbeatable growth opportunities, we are deeply invested in the future of our employees. Join us at Kiewit, where we go beyond construction to develop the ultimate road to success.

This position is based out of Lone Tree, CO office and may require travel as needed.

• Lead, mentor and develop a team of data engineers, solution engineers and data analysts — setting objectives, providing feedback, coaching and supporting career growth.
• Design and maintain scalable, reliable data solutions (pipelines, warehouses / lakes, streaming systems, APIs) that support business needs.
• Establish and enforce data governance frameworks, data lineage, metadata, and standards for data quality, integrity and usability.
• Ensure systems comply with regulations (e.g., privacy/security) and appropriately manage risk around the data solutions.
• Monitor and improve data quality, accuracy, completeness and readiness for analytics/insight consumption.
• Work with business stakeholders, analytics/data science teams, product owners, IT and other groups to translate business requirements into technical solutions and data capabilities.
• Communicate complex technical ideas in accessible terms; help the business understand trade-offs, constraints and opportunities.
• Plan, prioritize and oversee the delivery of data-solutions projects: from solution design through deployment, monitoring and improvement.
• Stay current with evolving data technologies, evaluate new tools/approaches (cloud, streaming, ML-ops, etc.) and drive improvements in architecture…