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Data Engineer - Construction Operations

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Onsite

Data Engineer - Construction Operations

Primoris Services Corporation

Data Engineer - Construction Operations

Skills

SQL QueriesData EngineeringPythonData ScienceKnowledge ManagementDatabricksGitData AnalysisMachine LearningAIGitHubPower BIAzure

5 days ago

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Important information


Contract type:

Permanent

Salary:

$80,000 – $105,000 / year

Location:

Denver, CO, USA

Work mode:

Onsite

Published on:

16 October 2026

What they need


Data Engineer

Renewable Energy Division

Position Summary

The Renewable Energy team is seeking a Data Engineer to develop and maintain the data infrastructure, analytics models, and business intelligence solutions that support project pursuit, estimating, engineering, procurement, and construction operations.

This role will focus on integrating and transforming historical construction cost data, labor productivity metrics, and project-specific attribute data into scalable data models that enable data-driven decision making. The ideal candidate will possess strong technical skills in Databricks, Power BI, Python, and SQL, while also demonstrating the ability to collaborate closely with estimators, engineers, project managers, and operational leaders.

The successful candidate will help build a modern data environment that converts years of project experience into predictive insights that improve bid accuracy, risk assessment, project planning, and overall business performance

Key Responsibilities

Data Engineering & Integration

  • Design, develop, and maintain data pipelines using Databricks, Python, and SQL.
  • Consolidate and transform data from estimating systems, project controls, ERP platforms, labor tracking tools, scheduling systems, and operational databases.
  • Develop and manage scalable data models that support historical cost analysis, labor productivity benchmarking, and project performance reporting.
  • Establish standardized data structures that improve consistency across projects and business units.
  • Ensure data quality, integrity, and traceability throughout the data lifecycle.

Construction & Preconstruction Analytics

  • Build datasets and analytical models leveraging:
  • Historical construction costs
  • Labor productivity performance
  • Equipment utilization metrics
  • Schedule performance data
  • Project execution outcomes
  • Site-specific and regional project attributes
  • Collaborate with estimating and preconstruction teams to identify cost and productivity trends that improve estimating accuracy.
  • Develop data solutions that support benchmarking, forecasting, and predictive analytics.
  • Enable analysis of key project drivers including geography, labor availability, engineering complexity, site conditions, contract structure, and execution strategy.

Business Intelligence & Reporting

  • Develop and maintain Power BI dashboards, semantic models, and reporting solutions.
  • Create executive, operational, and project-level reporting tools.
  • Deliver self-service reporting capabilities for business users.
  • Improve visibility into project performance and enterprise trends.

AI & Advanced Analytics

  • Support AI-enabled solutions that accelerate data discovery, forecasting, and decision making.
  • Utilize AI-assisted development and "vibe coding" techniques to accelerate solution delivery and automate repetitive development tasks.
  • Explore opportunities to leverage large language models and machine learning techniques for estimating, project benchmarking, and knowledge management.

Development & Collaboration

  • Work within a collaborative development environment utilizing GitHub for version control and code management.
  • Participate in peer reviews, testing, documentation, and continuous improvement initiatives.
  • Partner closely with estimating, engineering, procurement, project controls, operations, and executive leadership teams.
  • Translate business challenges into practical data solutions.

Required Qualifications

  • Bachelor's degree in Computer Science, Data Engineering, Construction Management, Engineering, Data Science, Information Systems, or related field.
  • 3+ years of experience in data engineering, analytics engineering, business intelligence, or related disciplines.
  • Strong hands-on experience with Databricks.
  • Experience developing Power BI reports, semantic models, and dashboards.
  • Advanced proficiency with Python and SQL.
  • Advanced Microsoft Excel capabilities.
  • Experience with GitHub and collaborative software development practices.
  • Experience designing data models for analytics and reporting.
  • Strong communication and stakeholder engagement skills.

Preferred Qualifications

  • Experience in renewable energy, EPC contracting, heavy civil, utility, industrial construction, or infrastructure industries.
  • Experience analyzing construction cost data, labor productivity, or project performance metrics.
  • Knowledge of estimating workflows and project controls processes.
  • Experience with Azure Data Services and cloud-based analytics platforms.
  • Familiarity with machine learning, AI, and Microsoft Copilot technologies.
  • Experience developing predictive cost or productivity models.

Desired Technical Skills

  • Databricks
  • Power BI
  • Python
  • SQL
  • GitHub
  • Excel
  • Data Modeling
  • ETL/ELT Development
  • Azure Data Platform
  • REST APIs
  • AI-Assisted Development
  • Machine Learning Fundamentals

What Success Looks Like

Within the first year, this individual will:

  • Establish trusted datasets for historical construction cost and labor productivity analytics.
  • Develop enterprise reporting and Power BI dashboards used by preconstruction and operations teams.
  • Improve estimate accuracy through data-driven benchmarking and trend analysis.
  • Create scalable data models that support future AI and predictive analytics initiatives.
  • Enable leadership teams to make faster, more informed business decisions using project performance data.

Target Salary 80,000 - 105,000

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