Senior Data Engineer
AIA Contract Documents • Remote
Posted: April 13, 2026
Job Description
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
Additional Content
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