Senior Data Analyst, Energy Preconstruction

Essential Job Duties And Responsibilities

• Cleanse, normalize, validate, and consolidate historical data on estimating, engineering, cost, productivity, procurement, project parameters, and project performance from spreadsheets, takeoff files, ERP/CRM systems, and other legacy sources.
• Build, maintain, and improve structured historical datasets and databases that support estimating benchmarks, conceptual pricing, root cause analysis, and future predictive modeling.
• Improve data quality and usability by resolving inconsistencies in naming conventions, units of measure, metadata, assumptions, and source traceability.
• Build and run queries against internal databases and enterprise systems; use SQL and other tools to extract, join, filter, validate, and organize data from multiple sources.
• Create repeatable query logic and data pipelines that improve accessibility, consistency, and auditability, while partnering with IT and data teams to align with governance standards and future data architecture.
• Identify correlations, trends, anomalies, and performance patterns across historical and active energy projects, including relationships among design variables, cost drivers, labor productivity, procurement timing, geography, weather, and project outcomes.
• Generate insights that improve profitability, reduce risk, strengthen conceptual estimates, and support value engineering and broader business decision-making.
• Benchmark current bids and conceptual estimates against historical project performance, market trends, prior wins, and known cost drivers; support the Indicative Lead and PCM in pricing and repricing exercises through structured data analysis.
• Develop dashboards, reports, and KPI visibility tools using Power BI or similar platforms to track estimate accuracy, cost variance, margin trends, bid competitiveness, win rates, and project milestones.
• Translate complex analysis into clear, decision-oriented reporting for leadership and business stakeholders.
• Support risk analysis, forecasting, sensitivity analysis, scenario modeling, contingency planning, and feasibility analysis using internal and external data, including location, weather, irradiance, and grid proximity.
• Support the improvement and standardization of estimating and engineering templates, define and reinforce data standards, act as a technical liaison across estimating, engineering, procurement, finance, and IT, and contribute to continuous improvement and future system integration.
• Perform other duties as assigned.

Education And Work Experience

• Bachelor’s degree in Data Analytics, Data Science, Engineering, Finance, Information Systems, or a related field is required.
• 5+ years of experience in data analytics or a related analytical role is required.
• Strong experience in cleansing, standardizing, and structuring complex datasets is required.
• Strong SQL proficiency and experience querying databases are required.
• Strong Excel proficiency is required; advanced Excel skills, including Power Query, PivotTables, and structured data manipulation, are preferred.
• Strong experience building dashboards and reports in Power BI or a similar tool is required.
• Experience in identifying correlations, patterns, and trends in data to support business decisions is required.
• Experience working independently and collaborating across business and technical functions is required.
• Experience supporting data governance, standardization, or system integration efforts is required.
• Knowledge of data quality, database concepts, query logic, enterprise data environments, dashboarding, KPI development, benchmarking, correlation analysis, trend analysis, and forecasting is required.
• Strong analytical, problem-solving, documentation, communication, and stakeholder collaboration skills are required.
• Experience in energy, EPC, construction, or infrastructure environments is preferred.
• Experience with ERP systems, such as Oracle, and CRM systems is preferred.
• Experience with Python or R for data analysis or automation is preferred.
• Familiarity with estimating, engineering, and procurement workflows is preferred.