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For Companies At a Glance
- Tasks: Ensure data accuracy and integrity through profiling, cleansing, and monitoring.
- Company: Join a fast-growing software company with a dynamic Data team.
- Benefits: Enjoy a competitive salary up to £45,000 plus fantastic extra perks.
- Why this job: Be part of a pivotal moment in data management and make a real impact.
- Qualifications: Strong SQL/BigQuery skills, Python experience, and a background in Data Quality required.
- Other info: Primarily remote work allows for flexibility in your schedule.
The predicted salary is between 36000 - 54000 £ per year.
Job Description
DATA QUALITY ANALYST
Up to £45,000 + BENEFITS
PRIMARILY REMOTE
Help shape the future of data at a pivotal moment for this company's growth.
THE COMPANY:
This software company has a growing Data team, and are looking for a Data Quality Analyst to help take advantage of their recent migration which has enabled them complete control over their data. They are now scaling fast and need someone dedicated to ensuring data accuracy and integrity.
THE ROLE:
A Data Quality Analyst will need experience in:
- Data profiling: spotting inconsistencies
- Data cleansing & transformation: standardising data
- Validation
- Monitoring & reporting
- Documentation
YOUR SKILLS AND EXPERIENCE:
A successful Data Quality Analyst will have the following skills and experience:
- Strong experience with SQL/BigQuery
- Experience with Python for automation
- Background in Data Quality and Governance
- Data Visualisation – ideally in Tableau
THE BENEFITS:
You will receive a salary, dependent on experience. Salary is up to £45,000 On top of the salary there are some fantastic extra benefits.
HOW TO APPLY
Please register your interest by sending your CV to Molly Bird via the apply link on this page.
Data Quality Analyst employer: Harnham - Data & Analytics Recruitment
Contact Detail:
Harnham - Data & Analytics Recruitment Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Quality Analyst
✨Tip Number 1
Familiarise yourself with the specific tools mentioned in the job description, like SQL and BigQuery. Being able to demonstrate your proficiency in these areas during any discussions will show that you're serious about the role.
✨Tip Number 2
Prepare examples of your past work related to data profiling and cleansing. Having concrete instances ready to discuss can help you stand out as a candidate who understands the practical applications of the skills required.
✨Tip Number 3
Brush up on your Python skills, especially in automation. If you can share how you've used Python to streamline data processes in previous roles, it will highlight your ability to contribute effectively from day one.
✨Tip Number 4
Research the company’s recent migration and how it impacts their data strategy. Showing that you understand their current challenges and opportunities will demonstrate your genuine interest in the role and the company.
We think you need these skills to ace Data Quality Analyst
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with SQL, BigQuery, and Python. Emphasise any previous roles where you focused on data quality, governance, or visualisation, particularly in Tableau.
Craft a Compelling Cover Letter: Write a cover letter that showcases your passion for data quality and your understanding of the company's recent migration. Mention specific examples of how you've ensured data accuracy and integrity in past roles.
Highlight Relevant Skills: In your application, clearly outline your skills in data profiling, cleansing, and transformation. Use bullet points to make these stand out and ensure they align with the job description.
Proofread Your Application: Before submitting, carefully proofread your CV and cover letter for any errors. A polished application reflects your attention to detail, which is crucial for a Data Quality Analyst role.
How to prepare for a job interview at Harnham - Data & Analytics Recruitment
✨Showcase Your Technical Skills
Make sure to highlight your experience with SQL and BigQuery during the interview. Be prepared to discuss specific projects where you used these tools to ensure data accuracy and integrity.
✨Demonstrate Data Profiling Knowledge
Be ready to explain your approach to data profiling and how you've identified inconsistencies in past roles. Providing examples of how you tackled these issues will show your practical understanding of the role.
✨Discuss Automation with Python
Since automation is key for this position, share your experiences using Python for data cleansing and transformation. Discuss any scripts or tools you've developed to streamline processes.
✨Prepare for Scenario-Based Questions
Expect scenario-based questions that assess your problem-solving skills in data quality and governance. Think of situations where you had to monitor, validate, or report on data quality and how you handled them.
