Data Engineer

About Our Product

Our technology lets you preview products in your own room before you buy them. Imagine you want to redesign your home and have been searching for new tiles for your kitchen, or a new rug for your living room. You definitely want to make sure it will look good in your space. We enable you to do that through our proprietary cutting‑edge technology, presented in an extraordinarily simple and accessible way.

Try our rug demo now! Simply upload a picture of your room using your mobile phone, and slide the rug under your coffee table:

You are a Data Engineer with a strong foundation in building and maintaining data pipelines and data models that power analytics, reporting, and product insights. You enjoy working close to production systems and care deeply about data quality, reliability, and performance.

You want to grow your impact and technical depth. You may not yet be setting a long‑term data strategy, but you are eager to take ownership of meaningful parts of the data platform, learn best practices in data warehousing, and work alongside senior engineers, ML engineers, and product teams to solve real business problems.

You value execution, collaboration, and learning, and you are comfortable operating in a fast‑paced environment where priorities evolve and ownership matters.

• Python, Django, Kubernetes, PostgreSQL, dbt, Redshift, AWS

• Design, build, and maintain reliable ELT pipelines that ingest and transform data into our centralized data warehouse.
• Model data for analytics and reporting use cases, ensuring performance, correctness, and usability for downstream consumers.
• Partner with Product, ML Engineers, Data Scientists, and Dev Ops to support data needs across the organization.
• Take ownership of specific data pipelines, datasets, or warehouse components, including monitoring, debugging, and iterative improvement.
• Help improve data quality, testing, and documentation standards within the data platform.
• Participate in system design discussions and code reviews, learning from senior engineers and contributing your perspective.
• Unblock and support internal stakeholders by making data accessible, understandable, and trustworthy.

• 2+ years of professional experience in data engineering, analytics engineering, or backend engineering with a strong data focus.
• Strong SQL skills and working proficiency in Python.
• Experience building or maintaining data pipelines and working with a data warehouse or analytics stack.
• Solid computer science fundamentals, based on a degree in Computer Science or equivalent practical experience.
• Understanding of system architecture with an emphasis on reliability, availability, and performance.
• Strong focus on execution and delivering production‑ready solutions.
• High attention to detail and commitment to data quality and long‑term maintainability.
• Clear communication skills and comfort collaborating across teams.
• Comfortable working in a fast‑paced, evolving environment where learning and adaptability are key.
• Familiarity with our stack is strongly preferred but not required.

Leap Tools is an equal opportunity employer committed to fostering an inclusive, equitable, and accessible environment. Accommodations are available on request for candidates taking part in all aspects of the interview process. If you require any accommodation, please contact us at

This is a net new position on the team.

Expected salary range, Ontario based: $65,000 - $115,000 + other benefits.