Senior Data Engineer

About Buildots:

Buildots is transforming construction management with AI and computer vision.

Our AI-powered SaaS platform automates on-site progress tracking, giving construction teams the tools to plan smarter, improve efficiency, and cut costly delays by up to 50%. The $13 trillion construction industry has seen little disruption in the past 150 years. Until now. Backed by leading VCs and industry pioneers, Buildots enables a new, performance-driven approach.

Deployed on hundreds of projects across North America, Europe and the Middle East, Buildots is already reshaping the future of the world's largest industry, and we're on track for rapid expansion in 2025.

Buildots’ customers include top global contractors, consultants and owners – Intel, Tidhar, Azrieli Group, VINCI Construction, Turner and Multiplex, to name a few.

About the Role

We’re looking for a Senior Data Engineer to join our growing data team and play a key role in shaping our data infrastructure and strategy. In this role, you’ll work closely with our System architect and data team to design and implement core data and ETL pipelines that will power analytics, product, and operational decision-making across the company.

This is a hands-on, high-impact position. Perfect for someone who thrives on tackling complex data problems, working directly with data analysts, and wants to have a direct influence on how data drives the business.

What You'll Do:

• Design and implement the core architecture for data infrastructure, ETL/ELT processes, and data modelling across multiple domains.
• Collaborate closely with Buildots’ System Architect to build reliable, scalable, and maintainable data pipelines using Python, dbt, and Airflow.
• Partner with analytics & engineering teams to translate business needs into solid technical data solutions.
• Architect and optimize our data warehouse to support advanced analytics, reporting, and business intelligence at scale.
• Model and structure data from multiple internal and external systems (e.g., Salesforce, Jira, Mixpanel) into clean, well-defined, and analytics-ready datasets.
• Implement robust data quality checks, monitoring, and validation frameworks to ensure data integrity and reliability.
• Proactively identify opportunities to optimize and scale data workflows and infrastructure.

Requirements:

• 5+ years of experience as a Data Engineer.
• Strong Python development experience for data processing and workflow orchestration.
• Advanced SQL skills and experience with data modeling and performance optimization.
• Hands-on experience with dbt and Airflow (or equivalent orchestration tools).
• Deep understanding of data warehouse architecture and modern data stack principles.
• B.Sc. in Information Systems Engineering, Computer Science, Industrial Engineering, or a related field.

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