Analytical Engineer — AI-Driven Data Pipelines (Hybrid)

Ageas UK; Reigate; Hybrid; GBP 65,000 - 90,000; Full time

Benefits offered by this job

Flexible Working

Health & Wellbeing Benefits

Competitive Pension

Employee Discounts

Job summary

Ageas is seeking an Analytical Engineer to join the Data & AI function in London, hybrid with occasional office attendance. You will design and deliver scalable data products, build robust data pipelines and collaborate with cross-functional squads to enable GenAI applications and analytics initiatives.

You will work with modern cloud platforms, SQL, Python and PySpark to optimise data flows, ensure data quality and support data-driven decision making across the business.

Qualifications

• Strong hands-on experience with modern cloud data platforms (Databricks or Snowflake) in AWS environments.
• Advanced programming and data engineering skills in Python, PySpark and SQL, with ETL pipelines.
• Experience in data modelling (end-to-end) including performance optimisation using DBT and SparkSQL.
• Experience with CI/CD, version control (Git, Jenkins) and pipeline orchestration tools such as Airflow.

Responsibilities

• Design, build and maintain scalable data products within esure’s industry-leading data platform.
• Develop and optimise data pipelines, ensuring high-quality, reliable datasets for analytics and AI use cases.
• Collaborate with product managers and cross-functional agile squads to deliver data-driven solutions, including GenAI applications.
• Integrate and transform data from multiple sources, ensuring data quality, governance and technical standards.
• Contribute to the continuous improvement of analytics engineering processes, tools and best practices.

Skills

Python

PySpark

SQL

ETL pipelines

Data modelling

Tools

Databricks

Snowflake

DBT

SparkSQL

Airflow

Git

Jenkins

Job description

Ageas is seeking an Analytical Engineer to join the Data & AI function in London, hybrid with occasional office attendance. You will design and deliver scalable data products, build robust data pipelines and collaborate with cross-functional squads to enable GenAI applications and analytics initiatives.

You will work with modern cloud platforms, SQL, Python and PySpark to optimise data flows, ensure data quality and support data-driven decision making across the business.