
Senior Platform Engineer
- London
- Permanent
- Full-time
- Build Technology enablers that move the needle on the domain's DORA metrics (such as cycle time, # deployments, change failure rate, mean time to recovery)
- Automate: Implement automation in provisioning, deployment, and scaling to minimise manual intervention and reduce errors.
- Standardise: Establish consistent environments and processes across the data & AI domain to help teams focus on value-driving activities, reduce complexity and improve reliability.
- Improve developer experience: Provide data governance tools, data ingest as a service, application/infrastructure interfaces and DevOps tooling to allow our engineers to focus on the application layer in their respective areas of expertise (e.g. ELT data modelling and transformations, building well-governed datasets, AI model building).
- Build scalable platforms: Design and build platforms that seamlessly promote best practice engineering for diverse user needs through a self-serve consumption model.
- Champion security and compliance: Embed security best practices and compliance requirements into the platform to protect data and meet compliance standards.
- Mentor: Upskill other platform engineers, data engineers and AI engineers to deliver and build adoption on your team's initiatives
- Cloud Data Warehouse - Snowflake
- AWS Data Solutions - Kinesis, SNS, SQS, S3, ECS, Lambda
- Data Governance & Quality - Collate & Monte Carlo
- Infrastructure as Code - Terraform
- Data Integration & Transformation - Python, DBT, Fivetran, Airflow
- CI/CD - Github Actions / Jenkins
- Business Intelligence - Looker
- Platform Engineering Expertise
- Extensive experience in platform engineering; designing, building, and maintaining robust and scalable components used for enabling key business initiatives.
- Deep understanding of automation principles and experience implementing automation for provisioning, deployment, and scaling.
- Strong advocate for standardization, with a track record of establishing consistent environments and processes.
- Software Engineering Practices:
- Experience with software development lifecycle (SDLC) best practices, including version control (e.g., Git), peer-reviewing, unit and integration testing, and continuous integration/continuous delivery (CI/CD).
- An automation-first mindset, where manual actions are reduced to exception-cases.
- A focus on building high-quality, maintainable, and well-documented code.
- Governance, Security & Compliance:
- Experience with tools used to bring data governance principles and practices to life (such as data catalogues, data quality monitoring, data contracts).
- Experience in embedding security and compliance into platform design and implementation.
- Collaboration, Communication and Thought Leadership:
- Exceptional communication and collaboration skills.
- Evidence of collaborative, pragmatic and value-based approaches to platform build-out.
- Experience mentoring and coaching junior engineers, fostering a culture of technical excellence within the team.