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Data QA - £68,000 - Permanent - Manchester (Hybrid 1 to 2 days per week in the office)
Please note: This role requires candidates to have the correct right to work in the UK. Ideally candidates will be able to commute to the office 1 to 2 days per week in either Manchester or London.
La Fosse has partnered with a financial services organisation to recruit a Data QA into their established data team. This is an exciting opportunity to join as the first dedicated Data QA, taking ownership of data quality assurance across a growing volume of incoming data, helping to mitigate risk and ensure the integrity, accuracy, and reliability of key business data.
Reasons to use Rodeo
I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?
Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.
Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.
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Grad scheme, placement, apprenticeship? Not sure what you want yet — that's fine. Your agent talks it through with you and turns "I have no idea" into a shortlist.
Graduate Consultant — 2026 Scheme
Why you're a good match
StrongYour economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.
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Every day your agent scans the market matching roles against what actually matters to you, not just keywords on a CV.
Why you're a good match
You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.
Experience fit
Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.
Only hits
No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.
Key responsibilities:
- Hands-on test automation experience using Python or similar technologies.
- Strong SQL skills for data validation, reconciliation, and root cause analysis.
- Experience testing data warehouses, data lakes, and ETL/data pipelines.
- Exposure to Azure data services and modern data platforms such as Synapse and Snowflake.
- Understanding of data quality, data integrity, and reconciliation testing.
- Knowledge of loan servicing and lifecycle data, including arrears, recoveries, and asset resolution.
- Strong experience across functional, regression, integration, and performance testing, with full defect lifecycle management.


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Interview Process:
- 1st stage: Technical Interview
- 2nd stage: Further Technical Discussion
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