Director, Data Engineering, ML & AI

Measurabl

1d•Remote

About The Position

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.

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+. 15+ years of hands-on and leadership experience for VP.
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
A combination of professional or educational experience (whether formal or informal) that affords you with the knowledge, skills, and abilities above

Nice To Haves

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

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