Senior Data Engineer – London Insurance Market | London (Hybrid)
To be considered for an interview, please make sure your application is full in line with the job specs as found below.
About the Role
We are hiring an experienced Senior Data Engineer to join a high-impact transformation programme focused on modernizing data platforms within the London Insurance Market. This is an excellent opportunity to work on cloud-native solutions that power underwriting, pricing, claims, reinsurance, regulatory reporting, and AI-driven analytics.
You will play a key role in designing scalable data architectures, building robust pipelines, and partnering with senior stakeholders across business and technology functions.
Location: London, United Kingdom
Working Model: Hybrid
Key Responsibilities
- Design and implement modern cloud-based data platforms using Medallion Architecture.
- Build and optimize batch and real-time data pipelines across underwriting, pricing, claims, reinsurance, and bordereaux data.
- Develop scalable solutions using Python, PySpark, Databricks, and/or Snowflake.
- Integrate data from policy administration systems, claims platforms, broker systems, third-party providers, and market feeds.
- Ensure strong data quality, reconciliation, lineage, governance, and auditability.
- Support analytics, MI, regulatory reporting, and AI use cases.
- Apply AI-assisted engineering tools (Open AI / Claude) to improve delivery productivity.
- Drive engineering best practices including code reviews, CI/CD, Git workflows, and automated testing.
- Mentor engineers and act as a trusted advisor to senior stakeholders.
Required Skills & Experience
- Proven experience as a Senior Data Engineer or Lead Data Engineer.
- Strong background in Insurance, ideally within the London Market ecosystem.
- Deep knowledge of underwriting, claims, delegated authority, pricing, and reinsurance.
- Hands-on expertise in Python, PySpark, Databricks, Snowflake, SQL.
- Experience with Azure, AWS, or GCP.
- Strong understanding of batch/streaming pipelines and data modelling.
- Familiarity with DevOps practices, CI/CD, and Git-based delivery models.
- Excellent communication skills with experience engaging business and technical stakeholders.
Nice to Have
- Experience with bank reporting / bordereaux processing.
- Exposure to GenAI use cases in engineering or analytics.
- Experience leading small engineering teams or workstreams.
Why Join?
- Work on business-critical transformation initiatives.
- Collaborate with senior leaders across Data, Underwriting, Finance, and Actuarial teams.
- Use modern cloud and AI technologies. xwzovoh
- Strong career growth in a specialist market domain.
Apply Now
If you have the right blend of Data Engineering expertise + Insurance domain knowledge, we’d love to hear from you.
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