4 of 4 Data Pipeline Jobs in Welwyn Garden City

About the role: The Data Quality Manager is responsible for ensuring that organisational data is accurate, complete, consistent, and fit for its intended use. The role provides leadership on data quality strategy, controls, and continuous improvement, enabling confident decision-making across reporting, analytics … operational processes.This role works closely with business, analytics, and technology teams to identify data quality risks, define controls, and drive sustainable improvements at source. It balances robust quality management with pragmatic delivery, ensuring data quality practices are embedded into everyday ways of working rather than treated ...

Senior Analytics Engineer on the Cyber Analytics team, you will lead the design and implementation of trusted, well-documented and tested data products that transform raw security data into reliable, accessible and actionable insights. These foundations will enable reporting, advanced analytics, machine learning, GenAI … powered analytics experiences to help security teams investigate, understand and respond to threats more effectively. Working closely with cross-functional security and data teams, you will ensure data is accurate, governed and fit for purpose, while helping to design and enable analytics agents that allow users ...

About the role: At Tesco Mobile, we’re passionate about connecting people—and data is at the heart of everything we do. We’re looking for a Senior Data Scientist to join our team and help shape smarter, more personalised experiences for our customers.If you enjoy … policies for full detailsYou will be responsible for: In this hands-on role, you’ll work on both static and time series data (including propensity models and forecasting models), developing innovative models that enhance customer experiences and drive business performance. From personalised communications and marketing optimisation to customer ...

assisted workflows in a human-accountable way. • Demonstrable understanding of AI governance, compliance, and responsible AI, including practical awareness of common failure modes (data leakage, bias, hallucination, unsafe automation) and how to implement guardrails. • Exposure to technical AI architecture and implementation, with the ability to review designs, challenge … assumptions, and guide engineers towards secure, maintainable solutions without requiring you to be a data scientist. • Demonstrable understanding of modern development lifecycles, including planning, design, build, test, deploy, operate, and continuous improvement, with an engineering-first approach to quality. • Exposure to secure and test-driven engineering, including threat ...