At a Glance
- Tasks: Lead the rollout of a Data Governance Framework and improve data quality across critical assets.
- Company: Join a collaborative team at a leading organisation focused on data governance.
- Benefits: Enjoy a hybrid work model, competitive salary, and opportunities for professional growth.
- Why this job: Make a real impact on data quality and governance while working with diverse stakeholders.
- Qualifications: Experience in data governance, management, and strong collaboration skills.
The predicted salary is between 56700 - 69300 £ per year.
The AA is seeking a Data Governance & Management Manager to lead rollout and ongoing maturation of the Data Governance Framework.
You will partner with stakeholders across privacy, information security and risk to improve data quality, definitions, ownership and lineage across critical assets.
You'll join a small, collaborative team, guiding governance activity, setting standards, and acting as a trusted escalation point for data governance, quality, and protection matters.
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Data Governance Manager (Hybrid) – Strategy & Quality in Basingstoke employer: The AA
At The AA, we pride ourselves on being an excellent employer, offering a structured development programme for Trainee Mobile Mechanics in Birmingham. With a starting salary of £28,000 and opportunities for pay increases as you progress, our supportive work culture fosters hands-on training and mentorship from experienced colleagues, ensuring you have the tools to build a rewarding long-term career in the automotive industry.
StudySmarter Expert Advice🤫
We think this is how you could land Data Governance Manager (Hybrid) – Strategy & Quality in Basingstoke
✨Get Involved in Data Science Meetups
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We think you need these skills to ace Data Governance Manager (Hybrid) – Strategy & Quality in Basingstoke
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at The AA, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at The AA. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at The AA
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
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Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
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✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
