Data Engineer

Overview

You will design, build, and optimise the enterprise data platform to turn raw data into actionable insights for strategic decision-making. You’ll work with business stakeholders, technical teams, and partners to support data-driven decisions and transform the data estate. This role sits at the core of a data transformation and modernisation journey, influencing architecture and reporting capabilities. You’ll engage across cloud environments and BI solutions to scale data solutions that unlock business value. Join a collaborative, growth-focused team shaping the future of data at scale.

Pay / Benefits

• competitive salary package
• generous private healthcare
• excellent pension
• hybrid working model
• opportunity to influence data function direction
• exposure to modern cloud technologies and large-scale data projects

Responsibilities

• Design and develop data pipelines, ETL processes, and data integrations
• Build and maintain data warehouse solutions and data repositories
• Develop robust data models, including fact and dimension tables
• Manage data quality, governance, lineage, and security
• Create and enhance reporting and BI solutions, including Power BI
• Support cloud-based data environments on Azure and AWS
• Collaborate with stakeholders to translate requirements into scalable technical solutions
• Contribute to evolving data strategy and architecture
• Support platform migrations and continuous improvement initiatives

Key requirements

• 5+ years in data engineering or similar data-focused role
• Strong SQL skills, including T-SQL
• Proven ETL experience with SSIS
• Scripting experience (Python or PowerShell)
• Knowledge of data modelling, warehousing, and dimensional modelling
• Experience with Azure and/or AWS
• Knowledge of Agile SDLC
• Experience designing scalable, secure, high-performing data solutions
• Excellent communication with technical and non-technical stakeholders
• Experience with Fabric, Databricks, Snowflake, DevOps, data migration, or financial services environments is advantageous

• excellent communication
• stakeholder engagement
• collaboration
• SQL / T-SQL
• SSIS
• Python or PowerShell

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