Requirements
- Cloud Infrastructure & Experience: 4+ years in cloud infrastructure engineering with hands‑on experience designing and administering complex platforms in GCP including working knowledge of networking (VPC, VPCSC, Direct Connect) and IaaS/PaaS architectural patterns.
- Designing and operating Google Cloud Platform - BigQuery, Dataflow, Dataproc, Cloud Storage, Pub/Sub - at production scale
- Infrastructure-as-Code using Terraform, with real hands‑on experience of multi‑environment configuration management across cloud providers
- GitLab CI/CD - building and maintaining pipelines, runners, and merge request workflows
- Cloud IAM and access control design, with a clear understanding of least‑privilege and security best practices
- Working collaboratively with data or ML engineering teams as a platform provider – not just building infrastructure, but making it usable
- A consultative approach. You’re comfortable working with non‑technical stakeholders, interpreting requirements, challenging assumptions where needed, and influencing outcomes without retreating into jargon
- (Desirable) AWS exposure
- (Desirable) Backstage experience – software catalog configuration, scaffolder templates, or plugin development
- (Desirable) Familiarity with data platform concepts – medallion architecture, lakehouse patterns, or orchestration tools such as Airflow or dbt
- (Desirable) Exposure managing Databricks
- (Desirable) Practical experience with AI coding assistants (Claude Code, GitHub Copilot, Cursor, or similar) in a professional engineering context
- (Desirable) Experience working in regulated financial services environments
What the job involves
- You’ll be joining a small, close‑knit Data platform engineering team of three to five engineers
- We’re a team that takes quality seriously, looks out for each other, and gets things done without a lot of ceremony
- Everyone brings something different across cloud infrastructure, data platform, and developer tooling and we rely on that range to solve problems well
- We work across time zones with colleagues in Bengaluru and Kraków, so clear communication and good async habits matter
- You won’t be siloed into a narrow lane in a team of this size, everyone gets exposure to the breadth of what we do, and everyone’s opinion on how we do it counts
- In a small team, a senior hire has an outsized impact - and this role is no different. Here’s what success looks like:
- You raise the floor. Your experience with GCP and AWS means the team spends less time firefighting and more time building. You bring rigour to how we design and review infrastructure, and your instinct for security and reliability makes the whole platform better
- You unblock people. Data engineers, ML engineers, and Data teams depend on the platform to move fast. You’re the person who understands what they need, builds the right foundations, and makes sure the platform is something people trust rather than work around
- You make the IDP real. An IDP is only useful if it’s kept alive and relevant. You’ll be one of the people who makes sure it reflects reality - that services are catalogued, templates are current, and engineers across the business can actually find what they’re looking for
- You help the team get smarter. Whether it’s sharing a better way to use AI tooling, writing a clearer runbook, or spotting a pattern we’ve been missing - you make the people around you better at their jobs
- You own your outcomes. This isn’t a team with heavy process or close supervision. You’ll be trusted to take work end‑to‑end, flag when something’s wrong, and drive improvements without being asked twice
- You speak the business’s language. The platform only matters if it delivers something the business can use. You'll spend real time with stakeholders across finance, compliance, BI and data science, understanding what they’re trying to achieve, framing the trade‑offs in language they can act on, and translating that back into platform decisions
- The best person in this role won’t just be technically strong - they’ll care about the team’s success as much as their own, and they’ll leave the platform in a better state than they found it
- Design and architect scalable cloud infrastructure, developing IaC solutions using Terraform and standardisation initiatives
- Build, optimise, and maintain CI/CD pipelines for infrastructure deployment, supporting DevOps and DevSecOps best practices across the organisation
- Operate and evolve GCP data platform services - BigQuery, Cloud Storage, Dataflow, Dataproc, Pub/Sub - in close collaboration with data and ML engineering teams
- Support IAM, service account design, and security posture across the platform, enforcing least‑privilege principles
- Lead incident response and root cause analysis for platform issues, and drive improvements to reduce recurrence
- Participate in an on‑call rota as the platform's operational coverage matures
- Contribute to the development and maintenance of our IDP - adding catalog entries, improving scaffolder templates, and keeping TechDocs accurate
- Work with data engineering and ML engineering teams to onboard their services and pipelines into the catalog, ensuring ownership and metadata are correctly represented
- Use AI‑assisted engineering tools - including Claude Code - as part of your daily workflow for infrastructure authoring, code review, and documentation
- Share effective AI patterns and prompting approaches with the team, helping build a culture of thoughtful, safe AI‑augmented engineering
