Why join us
Joining Sainsbury's as a Metadata & Data Quality Analyst offers a unique opportunity to play a pivotal role in enhancing data quality and driving impactful changes within the organisation. As part of our team, you will have the chance to manage and optimise the Group Data Catalogue, implementing data quality processes, and collaborating with stakeholders to ensure data integrity and value. With a focus on continuous improvement and innovation, you will be at the forefront of shaping data-driven solutions and contributing to the organisation's success. At Sainsbury's, you will be part of a dynamic and forward-thinking environment that values excellence, collaboration, and professional growth.
What you'll do
To drive and deliver the operational management of ‘assured data’ across the organisation, by progressing data quality improvements/controls and the Group Data Catalogue content and ownership, to ensure analytics, insights and decisions are based on validated data. The role will involve working across multiple teams, a mix of systems with a range of tools and technologies.
As a Metadata & Data Quality Analyst at Sainsbury's, your primary responsibility will be to manage and optimise the operational management of the Group Data Catalogue, ensuring that data quality is continuously improved through profiling, rule implementation, and triage processes. You will play a crucial role in developing and implementing data catalogue processes that enable users to work with data efficiently, supporting rapid discovery, prototyping, and data science initiatives that drive production solutions. Your role will involve identifying and prioritising artefacts for ingestion, maintaining the Group Data Catalogue, and collaborating with stakeholders to address data quality issues promptly and effectively. By facilitating source system data quality remediation and coordinating with the data ownership community, you will drive appropriate data quality improvements while prioritising and completing tasks within agreed timeframes.
What you need to know and show
As a Metadata & Data Quality Analyst at Sainsbury's, you are a meticulous and analytical professional with a deep understanding of data quality management and metadata analysis. With a focus on improving data quality and ensuring the integrity of the Group Data Catalogue, you possess the expertise to develop and implement data quality triage processes, identify root causes of data quality issues, and drive continuous improvement initiatives. Your ability to prioritise work effectively, collaborate with stakeholders across the organisation, and leverage technology for data cataloguing and profiling makes you a valuable asset in ensuring high-quality data standards and operational efficiency within the company.
Essential Skills:
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Advanced SQL with hands-on experience in Snowflake, including query optimisation, profiling, and schema management
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Hands-on experience with a data catalogue platform (Alation strongly preferred)
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Practical experience implementing or operating data quality rules, checks, and triage processes.
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Familiarity with data quality tooling (Alation Data Quality / Soda or equivalent).
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Understanding of metadata concepts: stewardship, ownership and classification.
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Awareness of data governance frameworks and their practical application
Desirable Skills:
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GitHub working knowledge
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Python scripting for automation, data quality checks, and pipeline integration
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GitHub for version-controlled configuration, pull requests, and CI/CD workflows
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Previous experience of creating reporting and visualisations, Power BI or other
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Awareness of Data Vault Modelling
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Understanding of design and development of data stores, digital solutions and data warehouses and associated toolsets.
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Data and information management lifecycles
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Knowledge and use of data quality methodologies, approaches, and processes
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How to undertake triage, root cause analysis and resolution- Desirable
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Understanding of JIRA- Desirable
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Understanding of Agile principles- Desirable
Skills and Behaviours
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Own it - takes full accountability for data quality issues through to resolution.
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Make it better - identifies opportunities to improve data availability that is trusted.
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Be human – Engaging with Senior Engineers and Architects to create standardised processes; builds great working relationships with colleagues (technical and non-technical) and shows care and respect to everyone.
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