Director, Data Engineering, ML & AI

Measurabl is a leader in ESG data management for commercial real estate, striving to create a sustainable and equitable world. The Director, Data Engineering, ML & AI will lead the data platform strategy, machine learning capabilities, and AI-powered product experiences, managing a team and driving the company's AI strategy.

Responsibilities:

• 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
• 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
• 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
• 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
• Define and execute annual strategic plan/focus and department OKRs aligned with company-wide AI and data strategy
• Partner with the CPTO and Directors across the company to translate business objectives into team strategy and actions
• Identify resourcing needs—including build vs. buy decisions for data and AI tooling—to meet current and future needs of the department and organization
• Manage vendor relationships and budgets for data infrastructure and AI/ML tooling

Requirements:

• 10+ years of hands-on experience in data engineering, ML engineering, or applied AI, with at least 3–5 years in a leadership role managing teams of 5+
• Education, whether formal or informal, in computer science, data science, engineering, or a related quantitative field
• Proven track record of shipping ML/AI-powered product features at scale in a SaaS or data-platform environment
• Demonstrated leadership experience and ability to drive team success across data engineering, ML, and analytics functions
• Previous experience managing large-scale data and AI projects that interplay with multiple teams and/or stakeholders
• Experience in commercial real estate, sustainability/ESG, cleantech, or regulated data environments is a strong plus
• Familiarity with ESG frameworks and standards such as GRESB, GHG Protocol, ENERGY STAR, CSRD, or TCFD is a plus
• A combination of professional or educational experience (whether formal or informal) that affords you with the knowledge, skills, and abilities above