Data Analyst, Customer Success

Cambio is a software platform for world-class real estate decarbonization. We help commercial real estate owners and tenants bring their real estate portfolios to net-zero using a powerful suite of software tools and AI-based recommendations. Our mission: to take the real estate industry into the climate action era. We are looking for team members who are excited about building great products that our customers love and working hard at a mission-oriented climate startup.

Our partners and investors include Y Combinator, Google, the U.S. Department of Energy, Stanford University and Fifth Wall. We are proud to be the fastest growing startup in our category. Join us on our mission to achieve net zero by 2050.

The Role

Decarbonizing real estate starts with precision-grade measurement and monitoring of asset performance, from energy to water. Cambio is automating the management of our customers’ carbon data by creating the world’s leading utility data and building systems platform.

We are expanding our team of Data Analysts to work closely with our Partner Strategy, Product, and Engineering teams to ensure high-integrity, production-ready data that powers analytics, reporting, and AI-driven recommendations.

As a Data Analyst at Cambio, you will own end-to-end data validation, transformation, and quality assurance for some of the world’s largest and most sophisticated real estate portfolios. You will work hands-on with large, real-world datasets—writing SQL, using Python for analysis and validation, and building repeatable workflows that scale. If you enjoy solving complex data problems, care deeply about accuracy, and want your work to directly support climate action, this role is for you.

What you will be doing

• 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.

Impact

With this role, you’ll have the opportunity to achieve the following accomplishments:

1. Lead the accurate measurement of energy, water, waste, and carbon data across a 500+ asset portfolio for a multi-billion-dollar real estate fund, enabling identification of 15%+ energy savings through Cambio’s platform.

2. Ensure the integrity of emissions data that powers AI-driven retrofit recommendations and portfolio-level decarbonization strategies.

3. Work directly with real estate owners to resolve data issues, saving customers 100+ hours of manual work and reducing portfolio data gaps by 25% or more.

Qualifications

• Strong quantitative background: 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. You are willing to roll up your sleeves to work with large, unstructured, and inconsistent datasets.

• Data-obsessed: You are meticulous and thrive when surrounded by numbers. You have a sharp eye for detail and can spot inconsistencies and anomalies in complex datasets.

• Analytical problem-solving: To you, cleaning and validating messy data is an exciting puzzle to solve. 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: Experience handling energy, utility, carbon, or real estate data is a bonus, but not required.
  

Requirements:

1. Must be based out of our New York or San Francisco hub

2. Have US work authorization

3. We are in office 3-4 days per week

Compensation:

The compensation for this role is consistent of cash, equity and benefits. Base pay for NY/SF based candidates is $100,000-105,000 annually