At a Glance
- Tasks: Ensure top-notch data quality and automate testing across a modern cloud platform.
- Company: Leading Financial Services firm with a focus on innovation.
- Benefits: Competitive daily rate, hybrid work model, and long-term contract until December 2026.
- Other info: Opportunity to enhance your skills in a collaborative environment.
- Why this job: Join a dynamic team and make a real impact on financial data quality.
- Qualifications: Experience in Data Quality Engineering, SQL, and financial data validation required.
The predicted salary is between 72000 - 88000 £ per year.
£500-525 per day | Outside IR35 | Initial contract to December 2026 | Hybrid (London)
Leading Financial Services business is looking to bring in a Senior Data Quality Engineer to join its Finance Data & Reporting Product Team. This is a hands-on contract focused on data quality, testing, reconciliation and automation across a modern cloud data platform. Working across the full data lifecycle, you will validate finance data from source systems through to Snowflake, dbt and Power BI, while enhancing an existing data quality framework and driving improvements in test automation and quality engineering practices.
Key Responsibilities
- Design and execute end-to-end data quality, validation and reconciliation testing.
- Validate data across source systems, Snowflake, dbt transformations and Power BI reporting.
- Enhance and extend the existing dbt Core testing framework.
- Build automated data quality, regression and reconciliation checks.
- Investigate data quality issues, perform root cause analysis and drive resolution.
- Partner with Finance, Product, Engineering and Business stakeholders to understand requirements and validate outcomes.
- Communicate testing results, risks and data quality issues to both technical and non-technical audiences.
- Create and maintain high-quality documentation, testing assets, process guides and knowledge transfer materials.
- Support the ongoing maturity of data quality and testing practices across the team.
You will be a senior data quality professional who can quickly understand existing frameworks, work independently, and add value from day one. You'll be equally comfortable writing SQL and reconciliation tests, discussing data issues with engineers, presenting findings to finance stakeholders, and creating documentation that enables others to support and extend the solution.
Essential Skills
- Proven experience in Data Quality Engineering, Data Testing or Data QA Engineering.
- Strong hands-on experience with Snowflake, dbt and SQL.
- Experience testing ETL/ELT pipelines and modern data warehouse solutions.
- Strong background in financial data validation, reporting and reconciliations.
- Experience within Insurance, Banking or Financial Services.
Senior Data Quality Engineer (Outside IR35) in London employer: Sanderson
As a leading Financial Services business, we pride ourselves on fostering a dynamic and inclusive work culture that prioritises employee growth and development. Our hybrid working model in London offers flexibility while you engage in meaningful projects that enhance your skills in data quality engineering. With competitive daily rates and a commitment to innovation, we provide an environment where your contributions are valued and your career can thrive.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Data Quality Engineer (Outside IR35) in London
✨Tap into Online Data Science Communities
Join online communities focused on data science like Kaggle, LinkedIn groups, or Reddit threads. These are goldmines for temporary gigs, as you can network with professionals and potentially hear about opportunities at companies like Sanderson before they're even advertised!
✨Show Off Your Skills With Projects
Got some cool data science projects? Showcase them on platforms like GitHub or create a personal portfolio website. This visibility is crucial for landing temporary roles—let recruiters see your actual skills in action, which can set you apart from the crowd.
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We think you need these skills to ace Senior Data Quality Engineer (Outside IR35) in London
Some tips for your application 🫡
Highlight Your Data Projects:When applying for a temporary data science role at Sanderson, make sure to showcase any relevant projects you've worked on. Whether it's a personal project, an academic undertaking, or contributions to an open-source initiative, detailing these experiences can really set you apart and demonstrate your practical skills.
Emphasise Your Analytical Skills:In your CV and cover letter, focus on the specific analytical skills that are key to data science. Mention any experience with statistical tools, programming languages like Python or R, and data visualisation software. Don't forget to include any certifications that may bolster your expertise!
Show Your Flexibility:Since this is a temporary role, it's important to convey your adaptability and willingness to learn. In your cover letter to Sanderson, emphasise how quickly you can get up to speed with new tools or projects. Highlight any previous experiences where you've had to adjust to new environments or challenges.
Craft a Unique Data-Driven Cover Letter:Instead of the usual generic cover letter, spice it up with some data! Maybe you’ve improved a process by 20% in a past role or cleaned a dataset with over a million entries. Use these stats to your advantage to grab Sanderson’s attention and show the tangible impact of your work.
How to prepare for a job interview at Sanderson
✨Showcase Your Analytical Skills
For a data science gig, it's crucial to demonstrate your analytical abilities. Be ready to discuss previous projects and the methodologies you used. Think about how you can quantify your impact—did your analysis improve efficiency or save costs? These are the stories that will stick with interviewers at Sanderson.
✨Brush Up on Technical Skills
You might face technical questions on tools relevant to data science, like Python, R, or SQL. Prepare to solve a problem live—perhaps they'll ask you to write a simple query or code snippet. It’s cool to talk about them, but we need to show we can do it in practice, especially in a temporary role where quick results matter.
✨Highlight Your Adaptability
Since this is a temporary position, emphasise your ability to learn quickly and adapt to new tools or workflows. Share examples of how you've thrived in fast-paced environments before, and how you can hit the ground running at Sanderson.
✨Prepare a Portfolio of Your Work
Bring your portfolio to the table—showcase projects where you've leveraged data science techniques to solve problems. Whether it’s a GitHub repository or a set of case studies, having tangible examples of your work will help you stand out and show what you bring to the team at Sanderson.
