At a Glance
- Tasks: Validate and ensure the quality of data across cloud-based platforms.
- Company: Join a leading enterprise focused on data excellence.
- Benefits: Competitive salary, flexible work options, and growth opportunities.
- Other info: Dynamic team environment with a focus on innovation and collaboration.
- Why this job: Make an impact by ensuring data accuracy in financial systems.
- Qualifications: Experience with Spark SQL, PySpark, and Azure data environments.
The predicted salary is between 36000 - 60000 £ per year.
We are seeking an experienced Data Tester to support end-to-end data validation, reconciliation testing, and data quality assurance across enterprise data platforms. The role involves validating operational and financial datasets across multiple data layers including ingestion, transformation, and reporting.
The ideal candidate will have strong experience with Spark SQL, PySpark, Databricks, and Azure-based data environments, with expertise in reconciliation testing, exploratory testing, and data validation for financial datasets.
Key Responsibilities- Perform end-to-end data testing across ingestion, transformation, and reporting layers within cloud-based data platforms.
- Execute data validation and reconciliation testing to ensure accuracy of operational and financial datasets including ledgers, claims, settlements, and transactional data.
- Design and implement data reconciliation testing strategies across multiple data sources and systems.
- Validate data transformations within Spark SQL, PySpark, and Databricks environments.
- Perform manual and exploratory data testing to identify data anomalies, inconsistencies, and quality issues.
- Investigate data discrepancies and collaborate with data engineers, business analysts, and product teams to resolve issues.
- Develop and execute test cases, test plans, and test strategies for data quality validation.
- Validate data pipelines and ensure accurate data movement across ingestion and transformation layers.
- Perform root cause analysis on data quality issues and recommend corrective actions.
- Support test automation where applicable using data testing frameworks and scripts.
- Strong experience in Data Testing / Big Data Testing / Data Quality Testing.
- Hands-on experience with Spark SQL, PySpark, and Databricks.
- Experience working with Azure data platforms.
- Strong experience in data reconciliation and financial data validation.
- Experience validating operational and financial datasets.
- Solid understanding of data ingestion, transformation, and data pipeline architectures.
- Experience in manual and exploratory testing of data systems.
- Ability to design and execute reconciliation test strategies.
- Strong SQL skills for data validation and investigation.
Data Test Engineer employer: Damco Solutions
Join a forward-thinking company that values innovation and excellence in data management. As a Data Test Engineer, you will thrive in a collaborative work culture that prioritises employee growth and development, offering opportunities to enhance your skills in cutting-edge Azure-based environments. With a commitment to quality and accuracy, our team supports meaningful projects that impact operational and financial datasets, making this an ideal workplace for those seeking rewarding and impactful careers.
StudySmarter Expert Advice🤫
We think this is how you could land Data Test Engineer
✨Tip Number 1
Network like a pro! Reach out to folks in the data testing field on LinkedIn or at meetups. We can’t stress enough how personal connections can lead to job opportunities that aren’t even advertised.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data validation projects, especially those involving Spark SQL and PySpark. This gives potential employers a taste of what you can do and sets you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on common data testing scenarios. We recommend practising how you’d handle real-world data discrepancies and discussing your experience with Azure-based platforms. Confidence is key!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who are proactive about their job search.
We think you need these skills to ace Data Test Engineer
Some tips for your application 🫡
Tailor Your CV:Make sure your CV highlights your experience with Spark SQL, PySpark, and Databricks. We want to see how your skills align with the role, so don’t be shy about showcasing your data testing expertise!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you’re passionate about data quality assurance and how your background makes you a perfect fit for our team at StudySmarter.
Showcase Your Problem-Solving Skills:In your application, share examples of how you've tackled data discrepancies or quality issues in the past. We love seeing candidates who can think critically and collaborate effectively with teams.
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’re considered for the Data Test Engineer role. Let’s get started!
How to prepare for a job interview at Damco Solutions
✨Know Your Data Tools
Make sure you brush up on your Spark SQL, PySpark, and Databricks skills. Be ready to discuss how you've used these tools in past projects, especially in relation to data validation and reconciliation testing.
✨Understand the Data Pipeline
Familiarise yourself with the end-to-end data pipeline process, from ingestion to transformation and reporting. Be prepared to explain how you ensure data quality at each stage and share examples of any challenges you've faced.
✨Prepare for Exploratory Testing Scenarios
Think about some real-world scenarios where you had to perform manual or exploratory testing. Be ready to discuss how you identified data anomalies and what steps you took to resolve them.
✨Collaborate and Communicate
Highlight your experience working with cross-functional teams, such as data engineers and business analysts. Show that you can effectively communicate issues and collaborate to find solutions, as this is key in a data testing role.
