SlipstreamJobs tracks this role from the company's public career site. Apply directly on the employer's site.
Funding Circle is a fintech platform that uses data-driven technology to provide small businesses with funding in minutes rather than weeks. The company operates with the agility of a startup combined with the stability of a public company, and has generated £7.2bn for the UK economy in the past year.
As Principal Data Engineer, you will be the primary technical authority for Funding Circle's Data Engineering and Data Platform architecture. Reporting to the VP of Data and serving on the Data Leadership Team, you will lead the analysis, architecture, design, and development of the company's Data and Analytics estate.
Key responsibilities include:
- Own and execute the Data Platform strategy and multi-phased roadmap for migrating to a Future State Data Platform on Snowflake and AWS, advising on migration architecture, transition states, historical data migration, and legacy decommissioning.
- Lead the architecture, design, and development of scalable cloud data warehouse, lakehouse, streaming, and analytics solutions.
- Define ingestion, transformation, and orchestration patterns, naming conventions, and structural standards, establishing clear publication boundaries between Product Engineering and Data Engineering.
- Identify, mitigate, and resolve architectural bottlenecks, control weaknesses, and technical debt across the data ecosystem.
- Own the Data as a Product Community of Practice, establishing standards for metadata, data contracts, schema design, data product versioning, data quality requirements, SLAs, SLOs, and semantic layer conventions.
- Champion data quality, lineage, observability, and governance, ensuring checks, SLAs, and alerting are expressed as code and monitored in production.
- Serve as a key member of the Data Architecture Review Board with formal decision rights over data architecture proposals, ensuring engineering viability and consistency with platform direction.
- Act as a technical bridge and mentor, training builders across the company to move from basic AI usage to sophisticated system creation and custom AI solutions.
The role is hybrid, based in London with 2 days per week in the office. The company offers flexible benefits, private medical and dental coverage, health assessments, digital GP access, life assurance, share schemes, financial coaching, annual learning allowance, electric car and cycle-to-work schemes, and award-winning parental leave policies.
REQUIREMENTS:
- Minimum 10 years of experience in Data & Analytics, with Staff, Principal, or equivalent roles in Data Engineering, Data Architecture, or Data Platform, ideally within digital products or FinTech.
- Extensive hands-on experience designing, building, and operating cloud data platforms on Snowflake and AWS, with proven track record leading complex, large-scale migrations from legacy systems.
- Experience designing data products across source-aligned, aggregate, and consumer-aligned patterns.
- Proven ability to architect and scale modern cloud data platforms using Snowflake, Apache Iceberg, Amazon Redshift, and S3.
- Hands-on expertise developing robust data transformation pipelines and orchestrating complex workflows using dbt and Apache Airflow.
- Strong track record automating infrastructure and deployment pipelines using Infrastructure as Code tools like Terraform and GitHub Actions.
- Ability to implement data governance, technical catalogues, end-to-end lineage, and data product portals to maximize data observability.
- Experience leveraging AI tooling to accelerate data engineering workflows, migrations, and platform readiness for AI applications.
- Experience establishing or leading a community of practice, driving standards adoption across teams.
- Proven track record of cross-functional partnership with Product, Engineering, Data Science, and Governance teams.
