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For Companies At a Glance
- Tasks: Ensure data accuracy and reliability while collaborating with a dynamic data team.
- Company: Join an innovative company working with Large Language Models.
- Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
- Why this job: Make a real impact on data quality and work with cutting-edge technologies.
- Qualifications: Experience in data QA and strong SQL skills are essential.
- Other info: Exciting environment with potential for career advancement and skill development.
The predicted salary is between 36000 - 60000 £ per year.
We are seeking a meticulous and analytical Data QA Analyst to join a new data team working with Large Language Models. You'll play a critical role in ensuring the accuracy, consistency, and reliability of our data. To ensure success as a data QA engineer, you should have programming skills and a keen eye for detail. Successful candidates will be evidently enthusiastic and motivated people who we can train up in our processes and ultimately play a key role in quality assurance initiatives across different stakeholder groups.
Responsibilities
- Develop and execute test plans, test cases, and scripts for data validation across ETL processes, databases, and reporting tools.
- Perform root cause analysis on data issues and work with engineering and analytics teams to resolve them.
- Monitor data quality metrics and implement automated checks to detect anomalies.
- Validate data transformations, aggregations, and business logic in dashboards and reports.
- Collaborate with data engineers, analysts, and product managers to define QA requirements and acceptance criteria.
- Document QA processes, test results, and data issue logs for transparency and continuous improvement.
SKILLS
Must have
- Proven experience in data QA, data analysis, or data engineering roles.
- Experience with MS SQL and PostgreSQL.
- Strong SQL skills for querying and validating large datasets.
- Familiarity with data warehousing concepts and ETL processes (hands-on experience with ETL pipelines, data warehouses, and data validation at scale).
- Understanding of data governance, data lineage, and metadata management.
- Excellent attention to detail and problem-solving abilities.
- Strong communication skills to explain data issues and collaborate with cross-functional teams.
- Scripting and automation (e.g., PowerShell, Python, Java).
- Experience with Gitlab.
- Knowledge of Spotfire data visualization platform or alternative dashboard solutions.
- Awareness of Agile delivery methodologies.
Nice to have
- Experience with cloud-based database solutions.
- Understanding of data lifecycle management and SOC2 security standards.
- Familiarity with geoscience disciplines, geospatial data and GIS tools (e.g., ArcGIS, QGIS) is advantageous.
- Experience with Python or other scripting languages for automated testing.
- Familiarity with cloud data platforms (e.g., Snowflake, BigQuery, AWS Redshift).
- Knowledge of data quality frameworks and tools (e.g., Great Expectations, dbt tests).
Senior Data QA Analyst employer: Luxoft
Contact Detail:
Luxoft Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Data QA Analyst
✨Tip Number 1
Network like a pro! Reach out to folks in the data QA field on LinkedIn or at industry meetups. A friendly chat can open doors and give you insights that job descriptions just can't.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data validation projects or any cool scripts you've written. This gives potential employers a taste of what you can do beyond just a CV.
✨Tip Number 3
Prepare for interviews by brushing up on common data QA scenarios. Think about how you'd tackle issues with ETL processes or data anomalies. We want to see your problem-solving skills in action!
✨Tip Number 4
Don't forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are proactive about their job search.
We think you need these skills to ace Senior Data QA Analyst
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience in data QA and analysis. Use keywords from the job description to show we’re on the same page about what you bring to the table.
Show Off Your Skills: Don’t hold back on showcasing your SQL skills and any experience with ETL processes. We want to see how you’ve tackled data issues in the past, so give us some solid examples!
Be Clear and Concise: When writing your cover letter, keep it straightforward. Explain why you’re excited about this role and how your background makes you a great fit for our team. We love enthusiasm!
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you don’t miss out on any important updates from us!
How to prepare for a job interview at Luxoft
✨Know Your Data Inside Out
Before the interview, brush up on your knowledge of data QA processes, especially around ETL and data validation. Be ready to discuss specific examples from your past experience where you ensured data accuracy and reliability.
✨Show Off Your SQL Skills
Since strong SQL skills are a must-have, prepare to demonstrate your querying abilities. You might be asked to solve a problem on the spot, so practice writing queries that validate large datasets and highlight any complex scenarios you've tackled.
✨Communicate Clearly
Strong communication skills are essential for this role. Practice explaining technical concepts in simple terms, as you'll need to collaborate with cross-functional teams. Think of examples where you successfully communicated data issues and how you resolved them.
✨Be Ready for Problem-Solving Scenarios
Expect to face hypothetical scenarios during the interview. Prepare to walk through your thought process for root cause analysis and how you would approach resolving data issues. This will showcase your analytical skills and attention to detail.
