Perform comprehensive data quality assurance and validation on large-scale utility and building performance datasets across multi-asset portfolios.
Write and optimize SQL queries to extract, join, validate, and analyze data from internal production databases.
Use Python to clean, normalize, validate, and analyze time-series utility data and identify anomalies, gaps, and inconsistencies.
Transform raw, unstructured data from utilities, building systems, and third-party providers into standardized, analytics-ready datasets.
Implement and execute data anomaly detection workflows, leveraging both internal tools and custom SQL/Python logic.
Partner closely with product and engineering teams to improve ETL processes and harden data pipelines.
Build and maintain complex Excel models and spreadsheets for data manipulation, analysis, and validation workflows.
Create and populate data templates for sustainability reporting frameworks including GRESB, TCFD, and CDP.

Requirements

2+ years of experience in data analytics, accounting, finance, or related quantitative field.
Advanced SQL skills: Comfortable writing complex queries involving joins, CTEs, window functions, aggregations, and data validation logic.
Python proficiency: Experience using Python for data analysis and transformation (e.g., pandas). Ability to write scripts to validate datasets and automate repeatable checks.
Advanced Excel skills required: You are highly proficient in Excel with experience in data manipulation, validation, complex formulas, and building analytical models.
Data-obsessed: You are meticulous and thrive when surrounded by numbers.
Analytical problem-solving: You have the ability to think creatively when addressing data quality challenges.
Collaborative team player: You work effectively with engineering and product teams to troubleshoot technical issues and improve data workflows.
Experience working with carbon or building data is a bonus, but not required.

Benefits

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

SQLPythonExceldata quality assurancedata validationdata analysisdata transformationETL processesanomaly detectiondata manipulation

analytical problem-solvingcollaborative team playermeticulouscreative thinkingattention to detail