Data Analytics Manager, Estimating Data Domain

Position Overview

The Data Analytics Manager for the Estimating Data Domain is pivotal in shaping and executing Kiewit’s data strategy within the estimating vertical. Positioned at the interface between the data services group and operational leaders, this role involves close collaboration with operations to identify and prioritize data analytics use cases, translating them into actionable roadmaps. The primary mission is twofold: to curate a rich, high-quality, sustainable data asset for the estimating domain and to build and nurture impactful data products and solutions. This role reports directly to the Sr. Director of Data Strategy within the Kiewit Data Services department. #LI-WJ1

If you are a motivated and experienced data analytics professional looking to make a significant impact in the construction industry, we invite you to apply for the position of Data Analytics Manager, Estimating Data Domain at Kiewit Corporation.

District Overview

At Kiewit, the scale of our operations is vast. Our construction and engineering projects span across the United States, Canada, and Mexico, improving and connecting communities with every initiative. We depend on our high-performing operations support professionals — they’re the glue that holds multiple areas of the business together and the catalysts that make things happen. We hire only the most driven people and offer them diverse career opportunities, strong leadership and mentorship, rewarding, collaborative work, and responsibilities they won’t find just anywhere else. We’re always pushing new limits. You can too. #LI-WJ1

Why Kiewit?

•    Opportunity to work with a leading construction and engineering firm.
•    Collaborative and innovative work environment.
•    Competitive salary and benefits package.
•    Professional growth and development opportunities.

Location

This position will be located at our office in Lenexa, KS. This is not a remote or hybrid position. 

Responsibilities

Strategic Planning:

• Source, identify, and prioritize data use cases within the estimating domain.
• Develop and maintain the data strategy and roadmap for the estimating function.
• Drive roadmap execution through building technical solves or via close partnership with the data engineering, software engineering, and data science teams

Stakeholder Management:

• Engage with stakeholders to understand their data needs and requirements.
• Articulate technical challenges and solutions in an accessible manner for non-technical stakeholders.
• Foster strong relationships with stakeholders, balancing exceptional customer service with effective stakeholder management.
• Ensure roadmap curation through bidirectional discussions, not unidirectional order-taking.

Data Quality, Reconciliation, & Governance:

• Monitor and improve data accuracy, consistency, and reliability within the estimating domain.
• Implement data quality processes, including data cleansing and validation.
• Investigate and resolve data discrepancies, collaborating with relevant teams to ensure data integrity.
• Establish and enforce data governance policies, standards, and best practices.
• Ensure compliance with regulatory requirements and data privacy laws.

Leadership and Collaboration:

• Hire, lead, and mentor a team of Data Analysts, providing guidance and oversight.
• Coordinate with other domain leads and technical teams to ensure cohesive data management efforts.
• Balance and prioritize competing initiatives, making strategic tradeoffs to maximize impact.

Business Acumen:

• Understand the holistic business landscape and assess the value of technical solutions.
• Align data initiatives with estimating business goals to drive economic or other forms of value to the organization.

Solution Design:

• Design high-level data solutions to meet business needs, working closely with technical teams (data engineering, software engineering, data science) for full-scale design and implementation.
• Ensure interoperability and alignment with the organization’s data architecture.

Product Management and Adoption:

• Partner closely with data engineering, software engineering, and data science to stay aligned on product development and implementation.
• Explain and promote new data tools to the business, driving user adoption.
• Collect feedback from users to improve and calibrate data tools.
   

Qualifications

• Bachelor’s degree in Data Science, Statistics, Computer Science, Engineering, or a related field. A master’s degree is preferred.
• Proven experience in a data analytics leadership role, preferably within the construction or engineering industry.
• Strong technical background including proficiency in data analytics tools and software (e.g., SQL, Python, Tableau, Power BI).
• Excellent analytical, problem-solving, and decision-making skills.
• Strong communication and interpersonal skills, with the ability to work effectively with diverse teams.
• Demonstrated ability to manage multiple projects and meet deadlines in a fast-paced environment.