Construction Management Data Analyst

Job Description

DPR Construction is seeking a Business Intelligence Analyst to support our Self Perform Work (SPW) entity within DPR. The SPW division directly hires and manages craft work forces to perform certain scopes of work, including concrete, drywall, electrical, interiors, waterproofing, and more. This role will serve as the primary data analyst for SPW, engaging with stakeholders across the group—including front‑line field supervisors, craft foremen, project managers, project executives, and corporate leadership.

The analyst will work closely with cross‑functional teams to build relationships, identify pain points, develop and drive data strategies, and deliver actionable insights. As part of the Data Analytics (DA) team, the analyst will help DPR move toward data‑driven decisions based on insights from integrated business processes, systems, and analytics.

• Collaborate with SPW business partners and other business units to align data analytics efforts with objectives and goals.
• Create, maintain, and execute the data analytics roadmap for SPW in alignment with overall goals.
• Drive conversations with stakeholders to fully understand and document pain points, focusing on successful outcomes and actions they aim to achieve.
• Develop and maintain relationships with business stakeholders, gaining a deep understanding of their processes, tools, and goals.
• Apply knowledge of construction management and self‑perform work to guide the development of data‑driven insights for SPW leaders and front‑line managers.
• Lead the development and implementation of solutions to current pain points, listening to diverse voices and creating long‑term, best‑in‑class solutions rather than quick fixes.

• Work with stakeholders to understand and align on business requirements.
• Create and maintain dashboards and apps as needed.
• Deliver actionable insights to improve business processes and drive strategic conversations.
• Track and monitor usage metrics to measure adoption and impact of analytics.
• Perform ad‑hoc analysis as required.

• Identify root sources of data integrity issues (report, DFL, data warehouse, source system).
• Troubleshoot and resolve data integrity issues in visualization tools.

• Create complex data models in visualization tools and perform necessary transformations.
• Query the data warehouse using SQL to analyze datasets quickly.
• Clean data as required.
• Identify potential new datasets to add to the data warehouse.
• Identify potential new integrations between source systems and the data warehouse.
• Collaborate with technical analysts to build requirements for DBT views and the data warehouse.

• Work with data engineering on the development and maintenance of the data catalog.
• Document queries, transformations, and refreshes for reports.

• Implement and enhance data security and governance guidelines.
• Create and maintain security for DFLs.
• Review requests and grant access to DFLs, reports, and apps as needed.
• Create and maintain row‑level security in visualization tools where required.
• Work with stakeholders to set security requirements for build and view access.

• Conduct impact analysis on reports when changes occur upstream.
• Communicate the impact to stakeholders and customers.

• Identify opportunities for data collaboration and integration across disciplines.
• Coordinate alignment across other T&I groups where applicable.
• Identify opportunities for AI/ML/Data Science initiatives and collaborate on delivery.
• Prioritize requests and initiatives with stakeholders based on business impact and resources.
• Participate in integrated work groups to align support functions.

• Train end‑users on interpreting dashboards and reports.
• Train end‑users on building reports themselves.
• Provide on‑the‑job training to business stakeholders when needed.
• Collaborate with data engineering to develop tools for self‑service analytics.
• Increase data literacy through targeted training and conversations.
• Identify…