Senior Cloud Platform Engineer

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. 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 make the IDP real. An IDP is only useful if it’s kept alive and relevant.
• 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 speak the business’s language. The platform only matters if it delivers something the business can use.
• 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.

Key Responsibilities:

• 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.