Technical Lead, Data Platform Engineer

London Source: WhatJobs

See advert for pay

Overview

In this role you will lead the Data Platform that serves all Funding Circle data teams, guiding the move to Snowflake and a Data as a Product model. You’ll transform target architecture into a clear engineering plan and drive alignment across teams. You’ll own platform quality, governance, and cost controls while enabling data scientists, analysts, and AI agents to build on the platform. You’ll mentor engineers and shape scalable patterns, contributing to a mission that fuels UK small businesses.

Pay / Benefits

flexible-first benefit allowance
private medical and dental
life assurance and share schemes
annual learning allowance
electric car and cycle-to-work schemes
season ticket loans

Responsibilities

Define and drive the engineering plan for the Data Platform and Snowflake migration
Own platform quality: Snowflake infra, RBAC, ingestion, orchestration (Airflow), CI/CD, observability, cost controls
Document and review technical decisions; escalate cross-domain issues
Grow and mentor the team; promote fast, deep code reviews and knowledge sharing
Define standards and reusable patterns to enable domain teams, Data Scientists, Analysts, and AI Agents
Ensure DP reviews do not block domain teams; collaborate with platform users
Oversee operational excellence: on-call quality, incidents, runbooks, disaster recovery
Maintain security and governance controls with Security and Data Governance
Manage relationships with platform vendors; handle support, escalations, and roadmaps
Communicate trade-offs to non-technical stakeholders; support AI-assisted engineering governance
Collaborate with the Principal Engineer to execute cross-domain architecture through the platform team

Key requirements

8+ years in Data & Analytics with architectural leadership experience
Deep Snowflake knowledge, ideally Iceberg/OpenTable formats and RBAC
Advanced SQL, Python, and enterprise-grade dbt development
Experience designing end-to-end data pipelines (batch, file-based, streaming with Kafka/CDC) using Airflow
Understanding of data security and governance, including PII handling and access control
Strong IaC and CI/CD skills
Proven ability to write clear design docs and communicate risks to non-technical stakeholders
Ability to design AI solutions and safe, scalable automated systems; mentor builders across the company
Experience bridging technical and non-technical teams; cross-domain collaboration