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ACD Direct

Senior Data Engineer

Posted Yesterday
Be an Early Applicant
Remote
Hiring Remotely in CAN
150K-180K Annually
Senior level
Remote
Hiring Remotely in CAN
150K-180K Annually
Senior level
Design, build, and maintain scalable Databricks-based ETL/ELT pipelines and data models optimized for AI/ML. Manage orchestration, data quality, governance, and CI/CD (ADO → GitHub) while collaborating with cross-functional teams in Agile delivery.
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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

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