Technical Lead, Data Platform Engineer
Role Overview
The Data Platform team builds and runs the platform used by Funding Circle data teams, including Snowflake, ingestion, orchestration, data contracts, and the Data Product Portal.
The company is moving to Snowflake and a federated Data as a Product model; this role leads platform engineering.
The role is based in London, is hybrid, and requires two days in the office.
Key Skills for This Role
Full Job Posting
Role and team
The Data Platform team builds and runs the platform used by Funding Circle data teams, including Snowflake, ingestion, orchestration, data contracts, and the Data Product Portal.
The company is moving to Snowflake and a federated Data as a Product model; this role leads platform engineering.
The role is based in London, is hybrid, and requires two days in the office.
Responsibilities
- Set technical direction and a sequenced engineering plan; own platform quality across Snowflake, RBAC, ingestion, orchestration, CI/CD, observability, and cost controls.
- Make and record decisions, mentor engineers, establish review standards, and support platform users with standards and reusable patterns.
- Lead platform work for the Snowflake migration, including source landing, reconciliation, cutover evidence, and legacy platform decommissioning.
- Own operational excellence, security, governance, vendor relationships, and clear communication of technical trade-offs.
- Establish safe AI-assisted engineering practices and translate cross-domain architecture into platform delivery.
What the role requires
- 8+ years in Data & Analytics and proven Senior/Technical Lead experience setting architectural direction.
- Deep hands-on Snowflake knowledge; advanced SQL, Python, and enterprise-grade dbt experience.
- Experience designing batch, file-based, and streaming data pipelines using Kafka/CDC and Airflow.
- Understanding of data security and governance, including PII handling and access control; strong infrastructure-as-code and CI/CD skills.
- Experience writing design documents, communicating technical risks, and making decisions under uncertainty.
- Ability to architect safe, maintainable AI solutions and mentor colleagues in AI system creation.
Desirable experience
- Iceberg/open table formats, data contracts (ODCS/ODPS), data product portals, lineage tools, regulated financial services, platform migration leadership, and PySpark or other distributed processing.
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