Data & ML Platform Lead

End Date Monday 02 November 2026

Salary Range £107,304 - £126,240

We support flexible working –

Flexible Working Options

Hybrid Working

Job Description Summary . Job Description

JOB TITLE:

Data & ML Platform Lead

SALARY: £107,304 - £126,240

LOCATION:

London

HOURS:

Full-Time

Our work style is hybrid, which involves spending at least two days per week, or 40% of our time, at one of our office sites. Colleagues with disabilities can be supported with workplace adjustments including hybrid working expectations in line with our Flexibility Works policy.

As a Data & ML Platform Lead, you will lead the team responsible for building and operating the infrastructure at the core of Curve’s business. You’ll own the platform supporting streaming and batch data ingestion, reverse-ETL, real-time decisioning for fraud and financial crime, and the ML and agentic AI capabilities increasingly used across the organisation. This is a hands‑on platform engineering role where you’ll lead and develop a multidisciplinary team while remaining closely involved in the most complex architectural challenges.

You’ll own the design and reliability of Kafka‑based decisioning services, data pipelines, orchestration, feature stores and underlying cloud infrastructure, ensuring the platform operates to bank‑grade standards of reliability, auditability and scale as Curve integrates into Lloyds Banking Group.

If you think all banks are the same, you’re wrong. We’re a pioneering, fast‑changing business that’s shaping finance as a force for good. If you’re after a role where you can have an impact and do the best work of your career, you’ve just found it

• Significant experience in data engineering, platform engineering or similar roles, including experience leading or providing sustained technical leadership to engineers
• Deep production experience with streaming technologies, ideally Kafka, and event‑driven architectures operating at scale
• Proven experience designing and operating production systems on GCP, including technologies such as Big Query, Managed Airflow, Cloud Run and Dataflow, or equivalent cloud infrastructure
• Strong programming ability in Python and experience with at least one systems language, ideally Go
• Experience building and operating real‑time services as well as batch and streaming data pipelines
• Experience with Terraform, Kubernetes and infrastructure as code
• Strong experience operating orchestration platforms such as Airflow reliably in production
• Experience deploying and operating ML systems in production, including feature stores, model serving or ML‑driven decisioning systems
• Experience designing reliable, observable platforms with clear SLAs, monitoring, alerting, load testing and capacity planning
• Strong understanding of operating technology within regulated environments, including audit trails, control evidencing, change governance and production systems with compliance implications
• Experience designing safe deployment approaches including feature flags, shadow modes, staged rollouts and reversible releases
• A track record of automating manual operational processes and building systems that are scalable, reliable and maintainable
• Strong leadership skills with the ability to set technical direction, delegate effectively and develop engineers into owners of the systems they operate

• Experience building or operating LLM and agentic AI workflows in production
• Experience with in financial crime, fraud, credit or risk decisioning environments
• Experience integrating technology platforms with large banking organisations or banking vendor ecosystems
• Hands‑on experience with Feast
• Experience with Snowplow
• Experi…