Data Operations Business Analyst

• Analyse large volumes of production data to investigate issues, anomalies, or questions raised by the team or data consumers.

• Identify and assess issues such as missing, duplicated, invalid, or incomplete data, including understanding scale, impact, and risk.

• Distinguish between historic data issues and ongoing problems.

• Use PySpark and SQL to explore data and validate assumptions.

• Present findings clearly and proportionately to support decision-making.

• Act as a point of support for data scientists and data engineers using the platform.

• Investigate concerns raised through queries or analysis conducted by others.

• Help users understand unexpected results, data behaviour, or platform constraints.

• Clarify whether issues represent defects, unsupported use cases, or gaps inunderstanding.

• Gather requirements from data consumers through one-to-one conversations and workshops.

• Facilitate discussions to understand different perspectives and needs across consumer groups.

• Translate outcomes into epics and tickets.

• Recommend priorities and sequencing, applying techniques such as MoSCoW.

• Balance consumer needs with data security and access controls.

• Strong analytical skills, with confidence working directly with production data.

• Experience using SQL and data analysis tools to investigate complex data questions.

• Ability to translate technical findings into clear, decision-focused narratives.

• Strong stakeholder engagement and workshop facilitation skills.

• Experience working in highly governed or regulated data environments.

• Ability to apply judgement about evidence, risk, and proportionate analysis.

• Interpret and apply complex data governance documentation.

• Identify platform changes that may require governance updates.

• Own or contribute to updates to governance artefacts.

• Support other teams in understanding governance boundaries and responsibilities.

• Identify and raise gaps or conflicts in governance arrangements.