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- Tasks: Enhance data quality and manage the Group Data Catalogue at Sainsbury's.
- Company: Join one of the UK's largest supermarkets with a dynamic marketing team.
- Benefits: Enjoy discounts, flexible working, and a competitive salary with great perks.
- Why this job: Make a real impact on data-driven solutions in a fast-paced environment.
- Qualifications: Advanced SQL skills and a passion for data quality management.
- Other info: Opportunities for professional growth and collaboration across diverse teams.
The predicted salary is between 36000 - 60000 £ per year.
We’d all like amazing work to do, and real work-life balance. That’s waiting for you at Sainsbury’s. We’re one of the biggest supermarkets in the UK with one of the largest websites. So marketing here really happens at scale. We move a lot faster than you’d think too, across Brand Planning, Brand Comms and Creative, Digital Marketing, CRM and Loyalty, Nectar 360, Insights, and Corporate Responsibility and Sustainability.
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.
What you’ll do:
- 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.
- 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.
- Develop and implement data catalogue processes that enable users to work with data efficiently, supporting rapid discovery, prototyping, and data science initiatives that drive production solutions.
- Identify and prioritise artefacts for ingestion, maintain the Group Data Catalogue, and collaborate with stakeholders to address data quality issues promptly and effectively.
- Facilitate source system data quality remediation and coordinate with the data ownership community to drive appropriate data quality improvements.
What you need to know and show:
- Advanced SQL skills
- Basic Python Skills
- Strong knowledge of the tools, technologies, skills and processes required to deliver a great data quality capability
- Well versed and able to demonstrate the concepts of metadata, stewardship, ownership, cataloguing and data quality
- Experienced with working with or being the consumer of a Data Cataloguing capability, such as Alation, Collibra or other
- GitHub working knowledge
- Previous experience of creating reporting and visualisations, using Tableau, Microstrategy, Power BI or other
- Awareness of Data Vault Modelling
- Understanding of design and development of data stores, digital solutions and data warehouses and associated toolsets.
- Data and information management lifecycles
- Knowledge and use of data quality methodologies, approaches, and processes
- Degree in a Mathematics and/or a Science discipline
- How to undertake triage, root cause analysis and resolution - Desirable
- Understanding of JIRA - Desirable
- Understanding of Agile principles - Desirable
Skills and Behaviours:
- Own it - takes full accountability for data quality issues through to resolution.
- Make it better - identifies opportunities to improve data availability that is trusted.
- 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.
We are committed to being a truly inclusive retailer so you’ll be welcomed whoever you are and wherever you work. Around here, there’s always the chance to try something new — whether that’s as part of an evolving team or somewhere else across the business - and we take development seriously and promise to support you. We also recognise and celebrate colleagues when they go the extra mile and, where possible, offer flexible working.
When you join our team, we’ll also offer you an amazing range of benefits. Here are some of them:
- Starting off with colleague discount, you’ll be able to save 10% on your shopping online and instore at Sainsbury’s, Argos, TU and Habitat, and we regularly increase the discount to 15% at points during the year.
- Pensions scheme and life cover.
- Performance-related bonus of up to 10% of salary, depending on how we perform.
- Annual holiday allowance and the option to buy up to an additional week’s holiday.
- Season ticket loans, cycle to work scheme, health cash plans, salary advance (where you can access some of your pay before payday) and access to a great range of discounts from hundreds of other retailers.
- Up to 26 weeks’ pay for maternity or adoption leave and up to 4 weeks’ pay for paternity leave.
Please see www.sainsburys.jobs for a range of our benefits (note, length of service and eligibility criteria may apply).
Metadata & Data Quality Analyst employer: Sainsbury's Supermarkets Ltd
Contact Detail:
Sainsbury's Supermarkets Ltd Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Metadata & Data Quality Analyst
✨Tip Number 1
Network like a pro! Reach out to current employees at Sainsbury's on LinkedIn or through mutual connections. Ask them about their experiences and any tips they might have for landing the Metadata & Data Quality Analyst role.
✨Tip Number 2
Prepare for the interview by brushing up on your SQL and Python skills. Be ready to discuss how you've used these in past projects, especially in relation to data quality management. We want to see your passion for data!
✨Tip Number 3
Showcase your problem-solving skills! Think of examples where you've identified and resolved data quality issues. This will demonstrate your ability to own it and make it better, which is key for this role.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, you’ll find all the latest roles and updates there, so keep checking back!
We think you need these skills to ace Metadata & Data Quality Analyst
Some tips for your application 🫡
Tailor Your Application: Make sure to customise your CV and cover letter for the Metadata & Data Quality Analyst role. Highlight your advanced SQL skills and any relevant experience with data quality management. We want to see how you can bring value to our team!
Showcase Your Skills: Don’t just list your skills; demonstrate them! If you've worked with data cataloguing tools like Alation or Collibra, mention specific projects where you used these tools. We love seeing real examples of your expertise in action.
Be Clear and Concise: When writing your application, keep it clear and to the point. Use bullet points for easy reading and make sure to address all the key responsibilities mentioned in the job description. We appreciate straightforward communication!
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way to ensure your application gets to us quickly and efficiently. Plus, you’ll find all the details you need about the role and our amazing benefits there!
How to prepare for a job interview at Sainsbury's Supermarkets Ltd
✨Know Your Data Inside Out
As a Metadata & Data Quality Analyst, you’ll need to demonstrate your understanding of data quality management. Brush up on your advanced SQL skills and be ready to discuss how you've used them in past projects. Be prepared to explain the importance of data integrity and how it impacts decision-making.
✨Showcase Your Problem-Solving Skills
Expect questions that assess your ability to identify and resolve data quality issues. Prepare examples of how you've conducted root cause analysis and triaged data problems in previous roles. Highlight your experience with tools like Alation or Collibra, as well as your basic Python skills.
✨Engage with Stakeholders
Collaboration is key in this role. Be ready to discuss how you’ve worked with various teams to improve data quality. Share specific instances where you’ve built relationships with technical and non-technical colleagues, showcasing your ability to communicate effectively across different levels of the organisation.
✨Demonstrate Continuous Improvement Mindset
Sainsbury's values innovation and improvement. Prepare to talk about how you've implemented processes for continuous data quality enhancement in your previous roles. Discuss any methodologies you’ve used and how they’ve led to better data availability and trustworthiness.
