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# Senior Data Engineer

- **Company:** Annapurna
- **Location:** London, UK
- **Experience:** Expert
- **Salary:** £50,000.0 - £55,000.0
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Cloud Computing, Data as a Services, Information Engineering, Data Warehousing, Monitoring of Systems, Python (Programming Language), Cloud Services, DataOps, SQL Databases, Data Streaming, AI Infrastructure, Data Ingestion, Snowflake, Enterprise Integration, Machine Learning Operations, Data Pipelines
- **Published:** September 10, 2026
- **Apply:** https://www.collegerecruiter.com/job/2840587126-senior-data-engineer

## About the Role

* 5+ years of experience in data engineering, ideally in a fast-paced product or platform environment
 * Strong experience with AWS cloud services and infrastructure as code
 * Proficiency in SQL, Python, and Snowflake
 * Experience building data pipelines (batch & streaming), APIs, and ML/AI infrastructure
 * Familiarity with DataOps practices, CI/CD pipelines, and modern orchestration tools
 * Strong understanding of data quality, schema evolution, and monitoring in production environments
 * A pragmatic mindset: you value speed and scalability but know where to invest for the long term

## Description

This is a senior-level opportunity for an experienced Data Engineer who is not only technically hands-on but also eager to shape the core data strategy of a fast-moving InsurTech company. You'll play a pivotal role in designing and developing robust, scalable data pipelines, AI/ML workflows, and APIs that feed data into every part of the business-from underwriter tools to financial systems.

You'll work in a modern, fully cloud-based stack (AWS, Snowflake, Python, SQL), with strong opportunities to influence architecture, automation, and data product direction across the company.

What you'll be doing

 * Design, build, and maintain robust, cloud-native data infrastructure and pipelines
 * Develop and manage metadata-driven data ingestion and transformation processes
 * Support AI and ML infrastructure in partnership with Data Science teams
 * Build APIs and data services to enable self-serve analytics and platform integrations
 * Optimise data warehouse performance and reliability (Snowflake)
 * Monitor data quality, pipeline health, and system observability
 * Partner with cross-functional teams to understand evolving data needs
 * Take ownership of key components and advocate for engineering best practices
 * Mentor junior engineers and contribute to a culture of learning and technical excellence


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