iO Associates
Senior Data Engineer

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The Role
As a Senior Data Engineer, you will:
- Design scalable data products within a cross-functional product team
- Act as a senior technical partner to product managers and lead data engineers
- Own complex, business-critical data products end-to-end
- Build and maintain high-quality data pipelines using Databricks & Spark
- Convert requirements into clear technical designs and conceptual data models
- Ingest large, complex datasets and automate manual processes
- Improve data quality, observability, reliability, and delivery performance
- Champion a build-once-consume-many culture across the platform
- Collaborate with stakeholders to solve data-related engineering challenges
- Contribute to engineering standards, best practices, and platform evolution
- Mentor other engineers and raise the overall engineering bar
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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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.
Tech Environment
My client is actively modernising their platform, moving away from legacy IaaS solutions and building a Databricks-first Lakehouse. Spark, Delta Lake, CI/CD, and modern DevOps practices are central to how they design and scale data products.
What You'll Need
- Strong hands-on experience with Azure Databricks & Spark in production
- 5+ years in data engineering or software engineering with a strong data focus
- Experience building production-grade pipelines on Azure
- Strong SQL and experience with analytical data models / data warehousing
- Proficiency in Python (Scala a bonus)
- Solid engineering discipline: CI/CD, testing, Git, DevOps for data
- Experience delivering enterprise-grade data products used by multiple teams
- Ability to communicate clearly with both technical and non-technical audiences
- Experience with Azure Synapse (dedicated/serverless SQL pools)
- Agile mindset; experience working in Scrum teams


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Nice to Have
- Hands-on experience with Docker, Kubernetes, or container orchestration
Contract Details
- Start: ASAP
- Location: London (with remote flexibility)
- Length: 6 months (likely extension)
- Rate: Competitive, depending on experience
“It took my CV and asked me questions relevant to understanding what kind of jobs to suggest for me. Suggestions were almost perfect. Jobs were exactly what I’ve been looking for.”
Jessica, London