Construction Management Data Analyst

DPR Construction is seeking a Business Intelligence Analyst to support our Self Perform Work (SPW) division. The SPW division directly hires and manages craft work forces to perform scopes of work including Concrete, Drywall, Electrical, Interiors, Waterproofing, and more. As the primary data analyst for SPW, you will engage with stakeholders—field supervisors, craft foremen, project managers, executives and corporate leadership—to build relationships, identify pain points, create data strategies, and deliver actionable insights that move DPR toward data‑driven decision making.

Responsibilities

Strategic Partnership / Roadmap / Execution / Delivery

• Collaborate with SPW business partners and cross‑functional teams to align data analytics efforts with business objectives.
• Create, maintain, and execute the SPW data analytics roadmap.
• Drive conversations with stakeholders to fully understand and document pain points, focusing on outcomes and appropriate actions.
• Develop and maintain relationships with business stakeholders, deepening understanding of their processes, tools, and goals.
• Apply knowledge of construction management and self‑perform work to guide the development of data‑driven insights.
• Be proactive in developing and implementing solutions to current pain points and building long‑term, best‑in‑class solutions.

Visualization / Storytelling

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

Troubleshoot Issues / Failures

• Identify root causes of data integrity issues across reports, DFLs, data warehouse, and source systems.
• Troubleshoot and resolve data integrity issues in visualization tools.

Data Modeling and ETL

• 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 and integrations for the data warehouse.
• Collaborate with Technical Analysts to build requirements for views in DBT and the data warehouse.

Documentation

• Work with Data Engineering to develop and maintain the data catalog.
• Create and maintain documentation of queries, transformations, and refresh schedules for reports.

Security / Governance

• Implement and enhance data security and governance guidelines.
• Create, maintain, and enforce security for DFLs.
• Review requests and grant access to DFLs, reports, and apps as needed.
• Create and maintain row‑level security in the visualization tool.
• Work with stakeholders to define and meet security requirements for build and view access.

Change Management

• Complete impact analysis for reports when changes occur to upstream source systems or tables.
• Quantify and communicate impacts to stakeholders and customers.

Coordination / Collaboration / Prioritization

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

Training / Data Literacy

• Train end‑users on interpreting dashboards and reports.
• Teach end‑users how to build reports independently.
• Provide on‑the‑job training to business stakeholders as needed.
• Collaborate with Data Engineering to develop and maintain self‑service analytics tools.
• Enhance data literacy across business stakeholders through targeted training and conversations.
• Identify opportunities to improve data literacy throughout DPR.

Data SME

• Operate as the subject‑matter expert for data availability, quality, processes, and technology.
• Maintain understanding of the data pipeline architecture, articulating its benefits and limitations.
• Ensure the source‑of‑truth system(s) are identified and operational.

Qualifications

• Master’s degree in Business…