Senior Data Engineer

About ACD For more than a century, AIA Contract Documents (ACD) has supported architecture, engineering, and construction professionals by delivering a shared industry standard to align parties on a project. What began in 1888 with the development of standardized construction contracts has evolved into a comprehensive suite of contract tools and foundational workflows that not only shape how the industry works today, but uniquely position ACD to help firms navigate construction’s growing complexity. In a world driven by scale, fragmentation, and AI-generated decisions that prioritize speed over a clear understanding of risk, ACD serves as a trusted anchor, ensuring project participants can reduce disputes and negotiations, while achieving faster alignment and more predictable outcomes for the future. AIA Contract Documents is seeking a Senior Data Engineer to support the buildout of data infrastructure powering upcoming AI initiatives. This role will play a critical part in designing and structuring data systems that enable scalable, high-quality inputs for AI and machine learning models. The ideal candidate brings deep experience in modern data engineering practices, strong familiarity with Databricks, and the ability to operate independently in a fast-evolving environment with limited oversight. Key Responsibilities Design and implement scalable data models optimized for AI/ML use cases, ensuring data is structured for effective model training and inference Architect and manage data pipelines using Databricks, including orchestration, job scheduling, and workflow optimization Develop and maintain robust ETL/ELT processes to support data ingestion, transformation, and delivery across systems Leverage Databricks Asset Bundles to manage deployment of data assets (pipelines, jobs, notebooks, and files) across environments Collaborate with cross-functional teams to align data architecture with AI initiative requirements and business objectives Ensure data quality, integrity, and governance standards are met across all pipelines and datasets Contribute to CI/CD practices using Azure DevOps (ADO), with a future transition to GitHub-based workflows Participate in Agile development processes, including sprint planning, stand-ups, and iterative delivery Other duties as assigned Qualifications 5+ years of experience in Data Engineering or related field Strong expertise in Databricks, including pipeline development, orchestration, and data architecture Experience designing data models to support AI/ML applications Proficiency in Python (PySpark) and SQL Hands-on experience with Azure-based data environments Experience with CI/CD tools such as Azure DevOps (ADO) Ability to work independently with minimal oversight and ramp quickly in a fast-paced environment Experience with Databricks Asset Bundles for deployment and environment management, preferred Familiarity with transitioning CI/CD workflows to GitHub, preferred Experience working in Agile development environments, preferred Exposure to AI/ML workflows and data requirements for model development, preferred What Success Looks Like Efficient, scalable data pipelines supporting AI initiatives Well-structured, high-quality datasets optimized for machine learning Streamlined deployment and orchestration of Databricks assets across environments Strong collaboration with stakeholders to deliver data solutions aligned with business needs