Staff Data Engineer

numi; Greater London; On-site; GBP 85,000 - 120,000; Full time

Job summary

numi is building a modern data platform and needs a hands-on engineer to design and deliver production-grade data pipelines and Databricks environments. You will shape architecture, implement scalable data workflows using Python, PySpark, and SQL, and collaborate with platform teams to raise reliability and security across data services.

You will work with IaC and automation tools, contribute to internal tooling, and help establish best practices for secure, compliant data products in a growing

Qualifications

• Hands-on experience building production-grade Databricks environments and pipelines with PySpark, Python, and SQL.
• Strong track record delivering modular, maintainable components with automated testing, Git workflows, and CI/CD.
• Experience securing data platforms with IAM, encryption, secrets management, least privilege, monitoring, and incident response.

Responsibilities

• Design, build, and maintain scalable data pipelines and data platforms.
• Define engineering standards and reusable patterns for data products.
• Ensure data security, governance, and reliability across environments.

Skills

Python

PySpark

SQL

CI/CD

Git workflows

Tools

Databricks

Terraform

GitHub Actions

DABs

Unity Catalog

Job description

Build and maintain scalable systems that collect, store, process, and analyse data - including data pipelines, data warehouses, and data lakes - ensuring all data assets remain accurate, accessible, and secure.

As a core member of the engineering team, you will play a key role in building a modern data platform for a growing enterprise. You will take a hands‑on approach to both shaping the overarching architecture and delivering initial data products. Working primary with Databricks and AWS, you will design and build production‑grade data pipelines, establish engineering standards, and create the reusable patterns, automation, and controls that form the foundation of the platform.

• Production Databricks & Data Pipeline Engineering: Hands‑on experience building production‑grade Databricks environments and reliable batch/streaming pipelines using Python, PySpark, and SQL.
• Software Engineering & Automated Delivery: Strong track record in creating modular, maintainable, and reusable components supported by automated pipeline testing, Git-based workflows, and CI/CD deployment.
• Secure Platform Engineering: Experience engineering data systems within secure or regulated environments, including identity and access management (IAM), encryption, secrets management, principle of least privilege, monitoring, and production incident resolution.

Preferred / Highly Valued Experience

• Unity Catalog Expertise: Practical experience configuring data lineage, access permissions, metadata management, and data governance via Unity Catalog.
• Infrastructure as Code (IaC) & Deployment Automation: Hands‑on experience with Terraform, Databricks Asset Bundles (DABs), and GitHub Actions or equivalent automated deployment tooling.
• Platform Product & Self‑Service Engineering: Experience creating internal developer tools, metadata‑driven automation, or paved paths that enable domain teams to build compliant data products independently.