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For Companies At a Glance
- Tasks: Analyse and ensure data quality while guiding best practices in data management.
- Company: Join a forward-thinking company dedicated to data excellence and innovation.
- Benefits: Enjoy flexible working options and a supportive team environment.
- Why this job: Make a real impact on data integrity and help shape data governance strategies.
- Qualifications: 3+ years in a data role with strong analytical and documentation skills required.
- Other info: Ideal for those passionate about data and eager to drive change.
The predicted salary is between 36000 - 60000 £ per year.
Minimum of 3 years experience working in a data role.
Capability to present and guide expectations aligned to Data Best Practice (DBP) Guidance.
Proficient in documenting data processes, data lineage and data management activities.
Excellent data analysis techniques.
Capable of creating and providing operational design and policy standards.
Good understanding of business data models for internal and external stakeholders.
Expertise in data profiling, data cleansing and data validation techniques.
Can identify impacts of data (or bad data).
Exposure to a range of visualization and reporting techniques to drive data integrity standards.
Data Governance and Quality Analyst employer: Career Wallet
Contact Detail:
Career Wallet Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Governance and Quality Analyst
✨Tip Number 1
Familiarise yourself with Data Best Practice (DBP) Guidance. Understanding these principles will not only help you in interviews but also demonstrate your commitment to maintaining high data standards.
✨Tip Number 2
Brush up on your data analysis techniques and be prepared to discuss specific examples of how you've used them in past roles. This will show that you can apply your skills effectively in real-world scenarios.
✨Tip Number 3
Gain a solid understanding of business data models and how they relate to both internal and external stakeholders. Being able to articulate this knowledge will set you apart from other candidates.
✨Tip Number 4
Get hands-on experience with data profiling, cleansing, and validation techniques. If you can share specific instances where you've improved data quality, it will greatly enhance your candidacy.
We think you need these skills to ace Data Governance and Quality Analyst
Some tips for your application 🫡
Highlight Relevant Experience: Make sure to emphasise your minimum of 3 years of experience in a data role. Use specific examples from your past work that demonstrate your capability in data governance and quality analysis.
Showcase Data Best Practices: Clearly outline your understanding of Data Best Practice (DBP) Guidance. Provide examples of how you've presented and guided expectations in previous roles, showcasing your ability to align with best practices.
Detail Your Analytical Skills: Discuss your proficiency in data analysis techniques. Include specific tools or methodologies you have used for data profiling, cleansing, and validation, as well as any relevant outcomes from your analyses.
Demonstrate Communication Skills: Since the role involves working with internal and external stakeholders, highlight your ability to document data processes and communicate complex data concepts clearly. Mention any experience you have in creating operational design and policy standards.
How to prepare for a job interview at Career Wallet
✨Showcase Your Experience
Make sure to highlight your minimum of 3 years' experience in a data role. Prepare specific examples of projects you've worked on that demonstrate your expertise in data governance and quality.
✨Demonstrate Data Best Practices
Be ready to discuss how you align with Data Best Practice (DBP) Guidance. Share instances where you've successfully implemented these practices in your previous roles.
✨Discuss Data Processes and Lineage
Prepare to explain your proficiency in documenting data processes and data lineage. Bring examples of how you've managed data management activities effectively.
✨Highlight Analytical Techniques
Show off your excellent data analysis techniques by discussing specific tools or methods you've used for data profiling, cleansing, and validation. Be prepared to explain how these techniques have improved data integrity in your past work.
