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COMPANY OVERVIEW Moss is a national, privately held construction firm providing innovative solutions resulting in award-winning projects. With regional offices across the United States, Moss focuses on construction management, energy EPC, and design-build. The company's diverse portfolio encompasses a wide range of sectors, including luxury high-rise residential, landmark mixed-use developments, hospitality, K-12 and higher education, justice, solar energy and battery storage, and sports. Moss is ranked by Engineering News-Record as the nation's top solar contractor and one of the top 50 general contractors. Moss prides itself on a strong entrepreneurial culture that honors safety, quality, client engagement, and employee development. Its employees consistently rank Moss as one of the best places to work. POSITION SCOPE AND ORGANIZATIONAL IMPACT Moss' Senior Data Analyst plays a critical role in transforming fragmented data across projects, engineering, cost, productivity, procurement, and performance into structured, actionable insights that enhance estimating accuracy, mitigate risk, and drive profitability within the Energy Preconstruction team. This role will lead to the development of a reliable historical dataset that supports benchmarking, conceptual pricing, forecasting, and strategic decision-making. Working with limited oversight, this individual will partner across preconstruction, procurement, finance, engineering, and IT to help create a single source of truth for preconstruction data. Through data cleansing, multi-system querying, dashboard development, and business analysis, this role will strengthen bid strategy, improve estimate confidence, identify cost and risk patterns, and support the long-term growth of a dedicated data function within 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. Develop 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. Build 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.
JOB TITLE: SENIOR DATA ANALYST, ENERGY PRECONSTRUCTION JOB LOCATION: FORT LAUDERDALE, FL CLASSIFICATION: FULL TIME - EXEMPT - SALARIED REPORTS TO: SENIOR MANAGER, SOLAR ESTIMATING Moss is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.
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Moss
May 22, 2026