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Data Engineer
Denver, CO 80207
$80k - $105k
2 weeks ago
💻 Open SourceExplicitly references "vibe coding" and AI-assisted development; mentions LLMs and Copilot to accelerate delivery.
About the Role
The Renewable Energy team is hiring a Data Engineer to build and maintain data infrastructure, transform historical construction and productivity data, and deliver Power BI reporting and predictive analytics to improve estimating, risk assessment, and project performance.
Job Description
Role
The Data Engineer will design, build, and maintain data infrastructure and analytics solutions for Primoris Renewable Energy. The role focuses on ingesting and transforming historical construction cost, labor productivity, and project attribute data into scalable data models, dashboards, and predictive analytics that improve bid accuracy, project planning, and operational decision making.
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 to support historical cost analysis, productivity benchmarking, and performance reporting.
- Ensure data quality, integrity, and traceability.
Construction & Preconstruction Analytics
- Build datasets and analytical models from historical construction costs, labor productivity, equipment utilization, schedule performance, and project attributes.
- Collaborate with estimating and preconstruction teams to identify cost and productivity trends and support benchmarking, forecasting, and predictive analytics.
- Enable analysis of project drivers (geography, labor availability, engineering complexity, site conditions, contract structure, execution strategy).
Business Intelligence & Reporting
- Develop and maintain Power BI dashboards, semantic models, and reporting solutions for executive, operational, and project-level needs.
- Deliver self-service reporting capabilities to business users to improve visibility into project performance and enterprise trends.
AI & Advanced Analytics
- Support AI-enabled solutions for data discovery, forecasting, and decision making.
- Utilize AI-assisted development and “vibe coding” techniques and explore LLMs and ML techniques for estimating, benchmarking, and knowledge management.
Development & Collaboration
- Use GitHub for version control and collaborate in peer reviews, testing, documentation, and continuous improvement.
- Partner with estimating, engineering, procurement, project controls, operations, and leadership to translate business challenges into data solutions.
Requirements
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.
- Hands-on experience with Databricks.
- Experience developing Power BI reports, semantic models, and dashboards.
- Advanced proficiency with Python and SQL and strong Microsoft Excel capabilities.
- Experience with GitHub, data modeling for analytics, and strong communication/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.
- Experience with Azure Data Services / cloud-based analytics platforms.
- Familiarity with machine learning, AI, and Microsoft Copilot.
- 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 and machine learning fundamentals
What Success Looks Like
- Trusted datasets for historical cost and productivity analytics established.
- Enterprise reporting and Power BI dashboards adopted by preconstruction and operations teams.
- Improved estimate accuracy through data-driven benchmarking and trend analysis.
- Scalable data models enabling future AI and predictive analytics initiatives and faster leadership decision making.
Benefits
- Paid company holidays
- Paid time off
- Medical, dental, vision, FSA/HSA
- Short-term and long-term disability
- 401(k) with matching contribution