Senior Data Engineer

• 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, 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.

• 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.