Lead Data Engineer

About Sidian

Sidian connects the drawings, models, documents, and decisions inside engineering firms so people and AI can work across them. We are a small Waterloo team backed by a US$1M pre-seed and working with global engineering firms.

The role

Design the pipelines that ingest drawings, BIM, PDFs, spreadsheets, documents, and project history, then unify them into a structured, queryable knowledge graph.

You will work directly with the founders and customers, own core architecture, and turn fast-moving AI capabilities into dependable systems.

What you will own

• Build and improve multimodal ingestion pipelines that transform drawings, BIM, PDFs, spreadsheets, documents, and project history into reliable, structured data.
• Architect and advance the company knowledge graph so engineering decisions across current and past projects are tracked, connected, and retrievable.
• Develop retrieval and reasoning systems on top of the graph that make this knowledge useful for search, recommendations, and automation.
• Design the data models and polyglot storage that hold heterogeneous engineering data together at scale.
• Work with customers to turn ambiguous engineering workflows into simple, dependable products.

What you bring

• Strong data engineering skills in Python, with sound judgment across backend and data systems.
• Hands-on experience with knowledge graphs and graph databases such as Neo4j and Cypher, including modeling complex relationships.
• Experience building production data pipelines over modern infrastructure including Apache Spark, Databricks, Parquet, and polyglot or multi-store architectures.
• Comfort ingesting and parsing messy, heterogeneous formats—including 3D/BIM, PDF drawings, Excel, Word, and email—into structured data.
• Evidence of initiative: an independent project, open-source contribution, research build, or startup you drove from idea to working system.

Apply

Compensation is to be determined and includes equity.