Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Data Engineer

Chaucer Group
City of London
4 days ago
Create job alert

Join to apply for the Data Engineer role at Chaucer Group.


About us

Chaucer is a leading insurance group at Lloyd's, the world's specialist insurance market. We help protect industries around the world from the risks they face. Our customers include major airlines, energy companies, shipping groups, global manufacturers and property groups.


Headquartered in London, with international hubs in Copenhagen, Dubai, Miami, Dublin, Singapore, Sydney and Bermuda, we are closer to our clients across the world. To learn more about us please visit our website www.chaucergroup.com


Job Profile Summary

We are seeking a skilled Data Engineer to join the Data Platform Team, working on the design, build, and optimisation of data pipelines and solutions on our Snowflake-based data platform. This role is critical to delivering robust, scalable, and efficient data solutions that underpin analytics and reporting across the organisation.


The Data Engineer will work closely with the Head of Data Platforms and the Data Engineering Lead, contributing to the execution of our data platform strategy and ensuring alignment with architectural standards, governance frameworks, and security requirements. This is a hands-on engineering role focused on technical delivery rather than line management.


Key Responsibilities

  • Design, develop, and maintain data pipelines and workflows using Snowflake, DBT, and related technologies.
  • Implement efficient data models (star and snowflake schemas) to support analytics and reporting needs.
  • Optimise SQL queries and transformations for performance and cost efficiency.
  • Automate data ingestion and transformation processes to ensure reliability and scalability.
  • Integrate Snowflake with upstream and downstream systems, including Azure services, legacy systems, and external data sources.
  • Collaborate with architects and engineering leads to ensure solutions align with enterprise architecture and security standards.
  • Contribute to the adoption of modern frameworks (e.g., FiveTran, ADF) to enhance platform capabilities.

Quality & Best Practices

  • Apply engineering best practices for coding, testing, and deployment, including CI/CD and automated testing.
  • Ensure data quality through validation, monitoring, and error-handling mechanisms.
  • Contribute to reusable patterns and frameworks for data engineering tasks.
  • Work closely with the Head of Data Platforms, Data Engineering Lead, architects, and delivery teams to translate requirements into technical solutions.
  • Troubleshoot and resolve data pipeline issues, providing timely support to stakeholders.
  • Participate in code reviews and knowledge-sharing sessions within the team.

Governance & Compliance

  • Implement and adhere to standards for data security, access control, and metadata management.
  • Ensure compliance with internal policies and external regulations such as GDPR.
  • Support data governance initiatives, including data lineage and quality frameworks.

Documentation & Enablement

  • Maintain clear documentation for data pipelines, processes, and engineering standards.
  • Support onboarding and enablement activities for new team members.

Skills and Competencies

  • Snowflake Expertise – Proven experience in developing, optimising, and tuning Snowflake solutions for performance and cost efficiency.
  • Data Engineering Proficiency – Advanced skills in SQL, DBT, and data modelling (including star and snowflake schemas) to deliver scalable, high-quality solutions.
  • Cloud Integration – Familiarity with Azure services and modern data engineering tools for seamless integration across platforms.
  • Governance & Compliance Awareness – Strong understanding of data governance, security, and regulatory requirements (e.g., GDPR).
  • Collaboration & Communication – Ability to work effectively in a fast‑paced environment and communicate complex technical concepts to both technical and non‑technical stakeholders.
  • Automation & DevOps Practices – Hands‑on experience with CI/CD pipelines, automated testing, and engineering best practices.
  • Domain Knowledge – Exposure to insurance or financial services data domains (desirable).
  • Problem‑Solving & Innovation – Strong analytical skills with a proactive approach to continuous improvement and innovation.
  • Technical Curiosity – Ability to stay current with emerging technologies and contribute to the evolution of the data platform.

Education

Bachelor's degree; industry certifications in business / data analysis or insurance domain desirable.


Why Join Chaucer?

Chaucer is a leading global insurer operating in both Lloyd's and company markets, helping industries worldwide manage risk—from nuclear, shipping, manufacturing, and property. Headquartered in London, with offices in Copenhagen, Bermuda, Sydney, Ireland, Miami, Dubai, and Singapore, we’re close to our clients wherever they are.


We have shown strong financial success with our Gross Written Premiums growing from $1.4bn in 2019 to $3.5bn in 2024. Backed by strong teams, platforms, and client relationships, Chaucer is poised for continued success.


Benefits

  • A flexible office hybrid work model that supports individual and team needs.
  • A diverse, inclusive culture that values people for who they are.
  • Extensive, non‑contributory benefits, including medical, life, and pension cover, flexible holidays, and wellbeing support.


#J-18808-Ljbffr

Related Jobs

View all jobs

Data Engineer

Data Engineer

Data Engineer

Data Engineer

Data Engineer

Data Engineer

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Machine Learning Hiring Trends 2026: What to Watch Out For (For Job Seekers & Recruiters)

As we move into 2026, the machine learning jobs market in the UK is going through another big shift. Foundation models and generative AI are everywhere, companies are under pressure to show real ROI from AI, and cloud costs are being scrutinised like never before. Some organisations are slowing hiring or merging teams. Others are doubling down on machine learning, MLOps and AI platform engineering to stay competitive. The end result? Fewer fluffy “AI” roles, more focused machine learning roles with clear ownership and expectations. Whether you are a machine learning job seeker planning your next move, or a recruiter trying to build ML teams, understanding the key machine learning hiring trends for 2026 will help you stay ahead.

Machine Learning Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK machine learning hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise shipped ML/LLM features, robust evaluation, observability, safety/governance, cost control and measurable business impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for ML engineers, applied scientists, LLM application engineers, ML platform/MLOps engineers and AI product managers. Who this is for: ML engineers, applied ML/LLM engineers, LLM/retrieval engineers, ML platform/MLOps/SRE, data scientists transitioning to production ML, AI product managers & tech‑lead candidates targeting roles in the UK.

Why Machine Learning Careers in the UK Are Becoming More Multidisciplinary

Machine learning (ML) has moved from research labs into mainstream UK businesses. From healthcare diagnostics to fraud detection, autonomous vehicles to recommendation engines, ML underpins critical services and consumer experiences. But the skillset required of today’s machine learning professionals is no longer purely technical. Employers increasingly seek multidisciplinary expertise: not only coding, algorithms & statistics, but also knowledge of law, ethics, psychology, linguistics & design. This article explores why UK machine learning careers are becoming more multidisciplinary, how these fields intersect with ML roles, and what both job-seekers & employers need to understand to succeed in a rapidly changing landscape.