Analytics Engineer - Cyber Data Platform

As the Analytics Engineer on the Cyber Analytics team, you will be responsible for transforming the raw data into organised, usable, well documented and tested data models. These data models will empower security teams to draw insights and develop reporting capability, advanced analytics, machine learning, and GenAI solutions to strengthen our security defences. You will collaborate closely with cross functional security and data teams to ensure the security data is reliable, accurate and accessible. At Tesco, we believe in the power of spending more time together, face to face, than apart. So, during your working week, you can expect to spend 60% of your time in one of our office locations or local sites and the rest remotely. We also recognise that life looks a little different for each of us. Some people are at the start of their careers, some want the freedom to do the things they love. Others are going through life-changing moments like becoming a carer, nearing retirement, adapting to parenthood, or something else. That’s why at Tesco, we always welcome a conversation about flexible working. So, talk to us throughout your application about how we can support. Data Integration and Transformation: Implement the ETL/ELTs to move data between the raw, trusted, and curated data layers of data lake supporting various real time and batch cyber use case. Data Modelling: Implement the logical and physical data model for the cyber data products to support threat detection, incident response and reporting. Coding and Documentations: Contribute to raising the quality bar of the team's codebase by producing high-quality code and documentation of data pipelines, data models and their quality metrics. Collaboration and Communication: Collaborate and communicate effectively with stakeholders and members of the data team and actively participate in monitoring and improving the data quality of the cyber data products. A strong passion for bigdata, data modelling, data quality and ETLs Proficiency in SQL and programming languages like Python Working knowledge of ETL and ELT frameworks, data modelling and orchestration tools like Airflow and dbt Experience working with cloud data platforms e.g. Databricks on Azure Good understanding of data lakes and data warehouses concepts Good practical understanding of version control systems such as Git Experience working with BI tools like Tableau Knowledge of cybersecurity principles and practices