At a Glance
- Tasks: Enhance data quality and governance using Snowflake in a global organisation.
- Company: Join a leading global organisation focused on data transformation.
- Benefits: Competitive salary, hybrid work model, and opportunities for professional growth.
- Other info: Collaborate with diverse teams and tackle exciting data challenges.
- Why this job: Make a real impact on data quality and governance in a dynamic environment.
- Qualifications: Strong Snowflake experience and knowledge of data governance principles required.
The predicted salary is between 60750 - 74250 £ per year.
A Senior Data Quality & Governance Engineer (Snowflake) is required to join a global organisation, supporting the development of its data governance, data quality, and data platform capabilities. This is a hands-on role focused on improving data quality, governance, ownership and trust in enterprise data, working closely with both technical and business stakeholders.
Key Responsibilities & Skills:
- Develop and implement data quality rules, controls, monitoring and remediation processes.
- Work with stakeholders to define Critical Data Elements, ownership models and data quality expectations.
- Support the development and implementation of data governance frameworks, standards and processes.
- Strong hands-on experience with Snowflake, including capabilities such as Horizon Catalog, Trust Centre, Metric Functions and Streamlit.
- Support data cataloguing, metadata, lineage and data quality management.
- Work closely with Data Owners, Data Stewards, Engineering and Platform teams to investigate and remediate data quality issues.
- Experience with Informatica CDGC, CDQ, dbt and Master Data Management would be highly advantageous.
- Strong understanding of data governance, data quality principles and frameworks such as DAMA-DMBOK.
The organisation is looking for a data professional with strong Snowflake experience alongside data governance and data quality expertise, who can operate confidently across technical and business teams. The successful candidate will have a hands-on approach, strong analytical and problem-solving skills, and the ability to translate governance requirements into practical data quality controls.
If you're an experienced Snowflake professional looking to play a key role in improving data quality and governance within a global data transformation programme, we'd love to hear from you.
Senior Data Quality (Snowflake) in Egham employer: Investigo
Join a leading organisation in the UK energy sector as a PMO Analyst, where you will thrive in a dynamic and supportive work culture that prioritises employee growth and development. With a hybrid working model based in Solihull, you'll benefit from flexible working arrangements, comprehensive training opportunities, and a collaborative environment that encourages innovation and continuous improvement. This role not only offers a chance to contribute to impactful change initiatives but also provides a pathway for career advancement within a well-respected company committed to excellence.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Data Quality (Snowflake) in Egham
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Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Investigo.
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We think you need these skills to ace Senior Data Quality (Snowflake) in Egham
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 Investigo, 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 Investigo. 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 Investigo
✨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!
✨Showcase Your Projects
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
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Investigo!
✨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.
