
Posted 1 day ago
Data Operations Business Analyst
AI Summary
The Data Operations Business Analyst works within a Data Ops team delivering a largescale data platform. The role focuses on analysing real production data, supporting downstream data users, shaping data-related requirements, and ensuring data is governed, understood, and used appropriately.
About this role
governed, understood, and used appropriately.
Key responsibilities:
Data analysis and investigation
• 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.
Supporting data consumers
• 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.
Requirements and prioritisation
• 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.
Data governance
• 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.
Skills and experience:
Skills and experience
• 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.
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