Senior Data Developer

📋 Description

• Own the data layer architecture across relational, columnar, and vector stores.
• Build scalable ingestion pipelines and star schemas for multi-system data.
• Design embedding pipelines and RAG context engine for AI agents.
• Transform data with deduplication and entity resolution for accuracy.
• Embed DataOps with automated tests, CI/CD, and observability.
• Implement data governance and AI security measures.

🎯 Requirements

• 5+ years data engineering; end-to-end data architecture experience.
• Snowflake and Databricks data warehouses.
• dbt, Airflow, Airbyte, Fivetran for ETL/ELT.
• Vector stores and embedding pipelines (pgvector, Pinecone, Weaviate).
• Dimensional modeling; Iceberg and relational/NoSQL storage.
• Python, Git, and CI/CD (Jenkins, GitHub Actions).
• AI security and data governance awareness.

🎁 Benefits

• Fixed hybrid work model: 3 days in office (Tue-Thu).
• Modern downtown office with gym and collaborative spaces.
• Annual All Hands in Vancouver HQ.
• Competitive salary and comprehensive benefits.
• Stock options and/or bonus eligibility.
• Generous paid time off and volunteering days.