Director, Data Engineering, ML & AI

About Measurabl

Measurabl has developed the leading ESG (environmental, social, governance) data management solution for commercial real estate—and we’re looking forward to doing so much more! Our team is a diverse group of innovators, leaders, and creators who are passionate about the work we do. We believe technology plays a central role in creating a sustainable, equitable world, and we’re working to build something that matters.

Overview:

The Director, Data Engineering, ML & AI is responsible for leading Measurabl’s data platform strategy, machine learning capabilities, and AI-powered product experiences. This is a transformational hands-on leadership role spanning data infrastructure, applied ML/AI, and sustainability-specific analytics. The Director or VP partners with the peer leaders, CPTO, and Product leadership to drive company-wide AI strategy, embed intelligence into the Measurabl platform, and position Measurabl as the definitive AI-powered sustainability intelligence platform in commercial real estate. This role leads a team of data engineers, software engineers, ML engineers, and data scientists, fostering a culture of technical excellence, experimentation, and sustainability-driven impact.

Essential Functions & Responsibilities:

The essential functions and responsibilities for this position include but are not limited to, the following. Other duties may be assigned as needed. 

Data Platform & Infrastructure

• Own and evolve Measurabl’s data platform architecture—warehousing, ETL/ELT pipelines, data quality frameworks, and data governance practices that underpin every product capability
• Drive data reliability and observability at scale, ensuring sustainability datasets are accurate, timely, and trusted by customers and internal teams alike
• Establish and enforce data contracts, lineage, and cataloging standards across the organization
• Evaluate and adopt modern data stack technologies (e.g., Snowflake, dbt, Airflow, Spark, Kafka) to optimize cost, performance, and developer experience
• Be able to work hands-on and coach engineers on improving via AI driven engineering.

Machine Learning & AI Product Features

• Define and execute the ML/AI product roadmap in close partnership with Product and Engineering leadership, identifying high-leverage opportunities to embed intelligence into the Measurabl platform
• Lead development of production ML systems including anomaly detection for utility data, predictive energy modeling, automated data extraction (OCR/NLP), and intelligent benchmarking
• Champion the responsible adoption of LLMs and generative AI across the product—from AI-assisted ESG reporting to conversational sustainability insights
• Establish MLOps practices including model monitoring, feature stores, experiment tracking, and CI/CD for models to ensure production reliability

ESG Data & Analytics

• Build and scale sustainability-specific data models, carbon accounting frameworks, and benchmarking analytics that differentiate Measurabl in the market
• Partner with Science and ESG teams to translate complex regulatory frameworks (GRESB, CSRD, GHG Protocol, ENERGY STAR) into scalable data products
• Enable advanced portfolio-level analytics and scenario modeling that help investors and asset managers make decarbonization decisions

People Leadership

• Drive department engagement and performance through hands-on leadership, mentoring, 1:1s, department collaboration, performance management programs, and engagement programs
• Foster a team culture focused on continuous improvement, learning, and development to ensure Measurabl is best positioned to deliver a world-class product
• Promote a transparent, data-driven culture of clear expectations and accountability
• Work with People Operations to identify strategies for growth, retention, and engagement within the Data Engineering and AI function
• Recruit, develop, and retain top talent in a competitive market; build a team that reflects the diversity of the communities we serve
• Foster cross-department communication with Product, Engineering, Science, Customer Success, and Go-to-Market teams to build a cohesive product and company culture

Business Management

• Define and execute annual strategic plan/focus and department OKRs aligned wi