Data Engineer

Description

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 are looking for our first dedicated Data Engineer — a self-motivated and proactive professional with a strong “can-do” attitude and a sense of ownership. This role involves taking responsibility across all data domains within the company, working closely with our analytics and development teams to build and maintain the data infrastructure that supports business needs. This position is ideal for someone ready to independently lead data engineering efforts and make a meaningful impact.

Responsibilities:

• Design, develop, and maintain scalable data pipelines and ETL workflows using tools such as Python, dbt, and Airflow.
• Architect and optimize our data warehouse to support efficient analytics, reporting, and business intelligence at scale.
• Model and structure data from multiple internal and external sources (such as Salesforce, Jira, Mixpanel, etc.) into clean, reliable, and analytics-ready datasets.
• Collaborate closely with our systems architect, analytics, and development teams to translate business requirements into robust and efficient technical data solutions.
• Monitor and optimize pipeline performance to ensure data completeness and scalability.
• Serve as a key partner and subject-matter expert on all data-related topics within the team.
• Implement data quality checks, anomaly detection and validation processes to ensure data reliability.

Requirements:

• 3+ years of hands-on experience as a Data Engineer or in a similar role.
• Expert-level SQL skills, capable of performing complex table transformations and designing efficient data workflows.
• Proficiency in Python for data processing and scripting tasks.
• Experience building and maintaining ELT/ETL pipelines using dbt.
• Hands-on experience with orchestration tools such as Airflow.
• Deep understanding of data warehouse concepts and methodologies, including data modeling.
• Self-motivated, capable of working autonomously while effectively collaborating with stakeholders to deliver end-to-end solutions.
• B.Sc. in Information Systems Engineering, Computer Science, Industrial Engineering, or a related field.

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Requirements