twentyAI
Data Platform Engineer | Early-Stage Financial Services Firm| TWE46293

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Company
An early-stage technology company developing next-generation data platforms for highly regulated industries. The team is building a greenfield platform from the ground up, giving engineers the opportunity to shape both the technology and engineering culture as the business grows.
Role
As the Data Platform Engineer, you will take ownership of the organisation's core data platform, ensuring data is accurate, traceable, and readily available across the business. You'll play a key role in designing and developing modern ingestion pipelines, scalable data infrastructure, and evidence capabilities that underpin analytics, reporting, and regulatory requirements.
You'll join a small, highly collaborative engineering team where you'll take ownership of major components of the platform and help establish the technical foundations as the business scales. This is a high-autonomy role with significant influence over architecture, engineering standards, and the future direction of the platform.
Working closely with engineering and product teams, you will help build resilient data services with a strong focus on quality, observability, and operational excellence.
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.
Responsibilities
- Design and implement end-to-end data ingestion pipelines using modern event streaming technologies across cloud and on-premise environments.
- Develop and maintain a scalable event lakehouse with strong data quality, lineage, and schema management.
- Build validation, reconciliation, and idempotency processes to ensure data integrity.
- Develop evidence and audit capabilities to support complete traceability of data flows.
- Implement monitoring, alerting, data freshness checks, and operational dashboards.
- Collaborate with engineering and product teams to deliver reliable, replayable datasets.
- Support AI-assisted data quality workflows and anomaly detection processes where appropriate.
- Continuously improve platform resilience, retention strategies, backup processes, and data accessibility.
Key Skills
- Strong experience building large-scale data ingestion and event streaming platforms.
- Expertise with technologies such as Kafka, Azure Event Hubs, or similar messaging platforms.
- Experience developing cloud-native and hybrid data pipelines.
- Strong understanding of lakehouse architectures and distributed data processing frameworks such as Spark.
- Experience with data modelling, schema evolution, lineage, and governance.
- Hands-on experience implementing data validation, reconciliation, and quality controls.
- Familiarity with observability tools such as OpenTelemetry or similar monitoring platforms.
- Experience building operational dashboards and monitoring solutions.
- Understanding of secure data access, retention, backup, and disaster recovery principles.
- Exposure to AI-assisted monitoring or intelligent data quality workflows would be advantageous.


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Benefits
- Opportunity to shape the architecture of a business-critical enterprise data platform.
- Join early and influence the technical direction of a greenfield product.
- High levels of ownership within a small, collaborative engineering team.
- Work with modern cloud, streaming, and data engineering technologies.
- Solve complex data engineering challenges with real business impact.
- Competitive salary and comprehensive benefits package.
Next Steps
If you are interested, please apply below or reach out directly isaac.salem@twentyai.com
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