Salary: £13,000 - 53,000 per year
Requirements: - Proven experience designing and building complex data models and distributed data pipelines, with a strong focus on data analysis, insight generation, and solving real-world business problems at scale.
- Advanced SQL skills for high-performance data transformation, exploration, and optimisation across large, complex datasets.
- Solid foundation in software and data engineering, including hands-on experience with CI/CD workflows, test-driven development, and agile collaboration.
- Bachelors or Masters degree in Computer Science, Software Engineering, or a related field.
- Demonstrated success delivering large-scale data warehousing solutions, including dimensional modelling and ETL pipeline design, ideally within Google Cloud Platform (GCP), with good working knowledge of DBT (Data Build Tool).
- Knowledge of how data is structured, processed, and applied within analytics and reporting environments.
- Ability to support the team in diagnosing and resolving data-related incidents, ensuring platform reliability and timely issue resolution.
- Bachelors or Masters degree in Computer Science, Software Engineering, or a related field.
- A natural collaborator with strong communication skills, capable of influencing technical decisions and contributing innovative ideas in a fast-paced, commercial environment.
- Knowledge of Snowflake, iceberg and lake house architecture.
- Experience working with Customer and Commerce data, third-party vendor report integration, exposure to Behaviour-Driven Development (BDD) principles, and familiarity with AI/ML concepts or practical experience applying AI in data workflows.
Responsibilities: - Design, build and support data models and distributed ETL pipelines using big data technologies on large-scale data sets.
- Collaborate with stakeholders from multiple business areas to understand business and data challenges, then develop requirements, specifications and recommendations for proposed solutions.
- Drive data engineering excellence by embedding DataOps principles and best practices into our work and becoming a go-to expert in one or more data domains.
- Tackle complex data challenges using tools like Google BigQuery, Python, SQL, and DBT, with opportunities to experiment and optimise through AI.
- Support and coach team members, share knowledge, act as a role model, and deputise for the Engineering Manager when needed.
- Work effectively across multiple GST workstream squads, embedding as needed to support delivery and provide data engineering expertise.
- Act as a bridge between various workstreams and the core SDP engineering organisation, ensuring alignment to platform best practices, data governance, and architectural principles.
- Support workstream squads onboarding data feeds, helping strengthen collaboration and reduce mismatches with upstream systems.
Technologies: - AI
- Big Data
- BigQuery
- CI/CD
- Cloud
- ETL
- GCP
- Support
- Python
- SQL
- Snowflake
- dbt
- Flow
More:
We are looking for a data engineering professional to help us shape scalable data solutions across multiple workstreams and business areas. You will work closely with stakeholders and agile squads, using modern tools and cloud-based technologies to improve our data platform, support governance and architecture standards, and help deliver reliable, high-quality data capabilities. We offer opportunities to collaborate, innovate, and apply AI where appropriate while working within a fast-paced commercial environment.
last updated 38 week of 2026