Senior Data Analyst, Energy Preconstruction

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 companys 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 nations 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

• Bachelors 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.