Senior Data Engineer at Chip

As a Senior Data Engineer at Chip, you'll help bring our data platform to the next level and empower Chip to be a truly data-driven business. You'll co-own the architecture of our data platform alongside our Analytics Engineer — not just implementing designs, but making the calls on how ingestion, modelling, and the semantic layer should actually work. You'll also provide technical leadership across the wider data engineering team as we grow.

What you can expect to be doing:

Architecture & Pipeline Design

• Design, build, and run scalable, secure data pipelines across multiple sources — with an eye on compute sizing and query performance
• Co-own architecture decisions across ingestion, modelling, and the presentation layer — defining how the platform should work, not just building to spec
• Design and evolve our medallion architecture (Bronze, Silver, Gold) as the platform matures

Engineering Standards

• Define more detailed engineering standards — naming conventions, partitioning, testing strategy, contract templates
• Apply Databricks best practices and Infrastructure as Code across the platform

Data Governance

• Own governance patterns in Unity Catalog — permissions, access models, and how we handle sensitive data
• Set technical governance standards the rest of the team builds against

Enablement & Self-Service

• Enable downstream consumers with self-service patterns, so the data team isn't the bottleneck for every request

Technical Leadership & Mentoring

• Provide technical leadership across the data engineering team — mentoring other engineers, reviewing code, and raising the engineering bar

What we’re looking for:

• Data engineering: You've built and scaled complex data products in a growing environment — you've seen platforms mature past their early ad hoc stage and know what that evolution actually takes.
• Databricks expertise: Deep, hands-on knowledge of the Databricks platform end to end — workspace and compute configuration, governance, orchestration, user management, engineering best practices.
• Data modelling: You're comfortable designing schemas and data models, including medallion architecture and Kimball/Star Schema concepts (Fact and Dimension tables), from the ground up.
• Git: You're fluent in Git workflows — branching, troubleshooting, code reviews.
• Python/PySpark/SQL: You write clean, efficient code across all three, and you understand how it performs at scale.
• Database management: Experience with SQL/NoSQL databases (e.g., Redshift, Postgres, MongoDB), with a solid grounding in database fundamentals — indexing, performance, design trade-offs.
• Terraform: You have experience in managing infrastructure as code with Terraform.
• Mentoring: You've supported and grown less experienced engineers before, and enjoy doing it.
• Architecture ownership: You design systems, not just implement them — you can reason through trade-offs and defend a decision.
• Data governance: You understand PII handling and governance patterns, and build them into your designs by default.