Data Engineer

Description

The role is an entry-level, hands-on data engineering position in the RE technology team, supporting data pipelines and data products used for business analytics, underwriting and decision-making.

You will work under Lead and senior Data Engineers, alongside Data Scientists, Product Owners and business stakeholders, on secure, reliable and cost-effective data solutions across cloud and on-premises platforms.

The focus is on learning core data engineering skills, delivering good work with support, and contributing to the Data Engineering Chapter while picking up good habits in data engineering, DevOps and automation.

The company is based in Bermuda and London and underwrites reinsurance risks worldwide for its own capital and for third-party capital. The team has over 100 people serving brokers and clients across a range of reinsurance products. Its approach is to match strong underwriting risk with globally diversified capital, backed by product-led underwriting and purpose-built analytics and systems.

Responsibilities

• Build and maintain data pipelines and data products across the data lifecycle, following well-defined tasks set by senior and Lead Data Engineers
• Help keep data accurate and accessible for analytics and reporting
• Deliver business value incrementally using agile methods
• Assist with proofs of concept and experiments
• Learn cloud data engineering and DevOps practices, including CI/CD and testing
• Build on platforms such as Snowflake, Azure and GCP
• Write clear, maintainable Python and SQL, plus dbt and orchestration tools
• Take part in code reviews and act on the feedback you receive
• Help monitor and troubleshoot pipelines
• Work closely with Data Engineers, Data Scientists and stakeholders
• Support Product Owners in delivering data solutions
• Take part in the Data Engineering Chapter and knowledge sharing
• Help business users understand their data
• Apply data governance, quality and security practices
• Support validation, lineage and monitoring within pipelines
• Write and update documentation for data products and pipelines
• Consider cost when designing solutions
• Help optimise pipelines for performance and scale
• Help monitor platform usage

Requirements

• A real interest in data and technology and a drive to build a career in Data Engineering
• Curiosity, a willingness to learn modern cloud technologies and engineering practices, and strong problem-solving instincts
• Communication skills to work well in a collaborative engineering team
• Suited to graduates, career starters, or people with early experience in data or software development
• Typically 1 to 2 years of experience in data engineering, software development or analytics, or equivalent exposure
• Working knowledge of SQL and basic Python programming
• Awareness of cloud platforms such as Azure or GCP, and of Snowflake
• Exposure to orchestration tools such as Prefect, Airflow or ADF is a plus
• Exposure to dbt or similar transformation tools is a plus
• Familiarity with source control, with interest in CI/CD and automated testing
• Basic understanding of data modelling concepts such as OLTP and OLAP
• Familiarity with structured and semi-structured data and exposure to SQL databases
• Willingness to own assigned tasks through to completion
• A practical approach to problem-solving and interest in agile environments
• Openness to feedback and coaching, and the ability to work in cross-functional teams
• Desirable: a degree in Computer Science, Engineering, Mathematics, Data Science or a related field
• Desirable: awareness of data governance concepts
• Desirable: exposure to BI tools such as Power BI or Dataiku
• Desirable: exposure to legacy tools such as SQL Server or SSIS

Conditions

Permanent position

Benefits

• Work alongside a team that the posting describes as unique in culture and full of strong people