Data Strategy & Engineering Lead

About the Role

Are you passionate about transforming raw data into real business impact? We're looking for a strategic, hands-on Data Strategy & Engineering Lead to architect the future of data at one of the nation's leading real estate companies. In this role, you'll do far more than build pipelinesyou'll drive a firm-wide transformation that empowers smarter decisions, accelerates AI integration, and unlocks the full value of our data.

As the firm's go-to data leader, you'll work cross-functionally with key stakeholders to understand business needs, build scalable infrastructure, and deliver insights that shape the direction of our company. You'll play a pivotal role in advancing our capabilities in generative AI, predictive analytics, and beyond.

What You'll Do

• Architect Our Data Future
• Evaluate current infrastructure and define a scalable, future-ready data strategy.
• Establish and maintain data governance, quality, and reliability standards.
• Build the Engine
• Design and develop robust ETL/ELT workflows for structured and unstructured data.
• Create and optimize data pipelines across cloud platforms (preferably Azure, but open to AWS/GCP).
• Use Python, SQL, and modern tools to turn messy data into business-ready intelligence.
• Collaborate and Deliver Impact
• Partner with teams across finance, leasing, operations, and development to understand their data needs.
• Build intuitive dashboards and reporting tools that bring data to life and support real-time decisions.
• Champion best practices for data entry, hygiene, and stewardship across the organization.
• Lead with AI & Innovation
• Help shape and lead generative AI initiativesfrom experimentation to implementation.
• Collaborate on building proprietary tools powered by machine learning and AI technologies.

Why You'll Love It Here

• High Impact: Play a critical role in a transformative company-wide data initiative.
• Cutting-Edge Work: Help shape how AI and predictive analytics redefine real estate.
• Cross-Industry Exposure: Collaborate across disciplines in a fast-moving, data-hungry environment.
• Growth Opportunity: Lead with autonomy and help set the data agenda from the ground up.

Requirements

• Bachelor's or Master's degree in Computer Science, Data Engineering, or a related field.
• 5+ years of experience in data engineering, analytics, or business intelligence.
• Deep experience with Microsoft Azure (Data Factory, Synapse, Azure SQL), or similar cloud platforms.
• Strong proficiency in Python and SQL; experience with dbt, Power BI, or Tableau is a plus.
• Proven ability to design and scale data infrastructure and pipelines.
• Excellent communicator with a knack for translating technical work into business value.
• Familiarity with generative AI, APIs (e.g., OpenAI), or LLM frameworks is a strong bonus.

About WS Development

Massachusetts-based WS Development is a mixed-use developer with a singular mission: creating places people want to be. With an approach that values art, science, innovation and, above all else, people, WS strives to engage each community it serves with best-in-class experiences, designed with our customers, tenants and partners in mind. Established in 1990, WS is one of few vertically-integrated real estate companies that conceptualizes, owns, operates and leases more than 100 properties that range from cutting-edge urban spaces to lifestyle and community centers. With over 22 million square feet of existing space and an additional nine million square feet under development, it is one of the largest privately-owned development firms in the country.

WS is where great ideas and great people come together to design, build, and operate some of the best loved real estate projects in the country. We live at the intersection of entrepreneurship and establishment. We have the infrastructure of decades supporting a culture of free-thinking excellence.

We expect every WS employee to feel welcomed and valued irrespective of race, color, religion, gender, gender identity or expression, sexual orientation, national origin, disability, age, veteran status, marital status, parental status, cultural background, and life experiences. Or for any other reason.