Senior Data Engineer

What you'll do:

• Build Scalable Data Solutions - Design, build and support Data Models & distributed ETL pipelines using big data technologies on large scale data sets.
• Deliver Impactful Data Features - Collaborate with our many stakeholders from multiple business areas to understand business and data challenges, thereafter, developing requirements, specifications and recommendations related to a proposed solution.
• Champion DataOps & Best Practices - Drive data engineering excellence by embedding DataOps principles and best practices into everything you do - becoming a go-to expert in one or more data domains.
• Solve Real-World Problems with Modern Tools - Tackle complex data challenges using tools like Google BigQuery, Python, SQL, and DBT, with opportunities to experiment and optimise through AI.
• Lead & Mentor - Support and coach team members, sharing knowledge and acting as a role model while deputising for the Engineering Manager when needed.
• Collaborate in Agile Squads - Work effectively across multiple GST workstream squads embedding as needed to support delivery and provide data engineering expertise.
• Shape the Future of Data at Scale - 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 using contributing to strengthening collaboration and reducing mismatches with upstream systems.

What you'll bring:

• Data Analysis & Engineering Expertise - 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.
• SQL Mastery - Advanced SQL skills for high-performance data transformation, exploration, and optimisation across large, complex datasets
• Engineering Best Practices - Solid foundation in software and data engineering, including hands-on experience with CI/CD workflows, test-driven development, and agile collaboration.
• Academic & Professional Credentials - Bachelor's or Master's degree in Computer Science, Software Engineering, or a related field.
• Cloud-Based ETL & Data Warehousing - Demonstrated success delivering large-scale data warehousing solutions, including dimensional modelling and ETL pipeline design-ideally within Google Cloud Platform (GCP) and good working knowledge of DBT (Data Build Tool) for building and managing data pipelines.
• Modelling & Data Flow Understanding - Knowledge of how data is structured, processed, and applied within analytics and reporting environments.
• Incident Support & Operational Readiness - Ability to support the team in diagnosing and resolving data-related incidents, ensuring platform reliability and timely issue resolution.
• Academic & Professional Credentials - Bachelor's or Master's degree in Computer Science, Software Engineering, or a related field.
• Team Collaboration & Innovation - 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
• Good to Have/Bonus Skills - 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