Lead, Data & ML Platform - Hybrid & Scale‑Oriented

Lloyds Banking Group; Greater London; Hybrid; GBP 107,000 - 126,000; Full time

Benefits offered by this job

Hybrid working

Generous pension contribution

Annual bonus

Share schemes

35 days holiday

Job summary

Lloyds Banking Group is seeking a Data & ML Platform Lead in London to head the core data/ML infrastructure, including streaming, real-time decisioning, and feature stores. You will lead a multidisciplinary team, shaping the platform to meet bank-grade reliability and auditability while integrating Curve within the Group.

The role requires strong leadership, deep experience in Kafka-based architectures, GCP, and production systems, with hands-on coding in Python and systems languages like Go.

Qualifications

• Significant experience in data engineering or platform engineering, with leadership of engineers.
• Deep production experience with streaming tech, ideally Kafka, and scale.
• Proven design/operation of production systems on GCP (BigQuery, Airflow, Cloud Run, Dataflow).
• Strong Python programming and experience with at least one systems language (Go).

Responsibilities

• Lead and own the data/ML platform architecture, including Kafka-based services and data pipelines.
• Oversee real-time and batch data processing, feature stores, and ML/decisioning components.
• Provide technical leadership, build a reliable, auditable platform aligned with bank-grade standards.

Skills

Data engineering

Platform engineering

Kafka

GCP

Python

Go

Data pipelines

ML systems

Cloud infrastructure

Leadership

Tools

BigQuery

Managed Airflow

Cloud Run

Dataflow

Terraform

Kubernetes

Airflow

dbt

Feast

Snowplow

Job description

Lloyds Banking Group is seeking a Data & ML Platform Lead in London to head the core data/ML infrastructure, including streaming, real-time decisioning, and feature stores. You will lead a multidisciplinary team, shaping the platform to meet bank-grade reliability and auditability while integrating Curve within the Group.

The role requires strong leadership, deep experience in Kafka-based architectures, GCP, and production systems, with hands-on coding in Python and systems languages like Go.