2 of 2 Data Engineer Jobs in the City of Westminster

Job Title: Senior Data Engineer Location: London Victoria, Hybrid Reports to: Engineering Manager A bit about us At nudge we believe people need to be in control of their finances. nudge puts you in control of your money. Combining behavioural psychology, data, and personalised education, our financial wellness benefit empowers people to develop their financial skills and … and PepsiCo, to support the financial wellbeing of their employees. About the team Our team is united by the shared purpose to create brighter financial futures for everyone, everywhere. Data is at the heart of our decision-making. You’ll work closely with product, data, infosecand engineering teams. Role purpose You will be instrumental in designing and building … scalable data infrastructure, pipelines, and tooling to support advanced analytics, real-time data applications, and regulatory compliance. This is an opportunity to make a meaningful impact on the lives of thousands of people across the globe. What will you be doing? Things move fast at nudge, and we are always learning. This means we need to stay agile More ❯

D&A capabilities and maintain them. Partnerships with other teams such as Supply, Manufacturing & R&D are also key to ensure process alignment and shared value creation. As a Data Engineer in the Commercial team, your key responsibilities are as follows: 1. Technical Proficiency: Collaborate in hands-on development using Python, PySpark, and other relevant technologies to create … and maintain data assets and reports for business insights. Assist in engineering and managing data models and pipelines within a cloud environment, utilizing technologies like Databricks, Spark, Delta Lake, and SQL. Contribute to the maintenance and enhancement of our progressive tech stack, which includes Python, PySpark, Logic Apps, Azure Functions, ADLS, Django, and ReactJs. Support the implementation of … DevOps and CI/CD methodologies to foster agile collaboration and contribute to building robust data solutions. Develop code that adheres to high-quality standards, promoting a scalable and maintainable data platform. 2. Learning and Growth; Contribution to Solutions: Collaborate with the team to learn and apply the best practices in data engineering. Actively participate in engineering More ❯