Role Overview
- Build digital-first, data-driven customer experiences that simplify the organisation while keeping data secure
- Design and deliver innovative data solutions using pipelines, modelling and ETL frameworks
- Enable commercial success through actionable insights and scalable, streaming data ingestion solutions
- Drive transformation by advocating improvements to data structures, metrics and platforms
Key Responsibilities
- Develop a comprehensive understanding of enterprise data structures, metrics and dependencies
- Design and deliver transformation solutions, including complex data extractions and integrations
- Build cost-effective, strategic data solutions by understanding and optimising data platform costs
- Source new data using appropriate tools and integrate it into end-to-end data solutions
- Drive customer value by translating complex business requirements into reusable data engineering solutions
- Participate in the data engineering community to support strategic initiatives and best practices
- Build scalable data architectures and transform data to make it usable for analysts and data scientists
- Automate data engineering pipelines by removing manual processes and improving reliability
- Lead planning and design of complex data products and provide technical guidance to peers
Required Experience & Capabilities
- Strong understanding of data usage, dependencies and customer impact across teams
- Experience extracting value and features from large-scale data sets
- Proven experience in ETL technical design, data quality testing, cleansing and monitoring
- Hands-on experience with data sourcing, exploration, analysis, warehousing and data modelling
- Experience developing data solutions using Python or Java
- Strong understanding of data lake and data warehouse architectures
- Experience working with cloud platforms such as AWS, Azure or GCP
- Proficiency in SQL, Hive, Parquet and Delta Lake
- Experience using Git, version control, CI/CD pipelines and Agile methodologies
