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Apache Data Engineer (SC Cleared)

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Job Title: Apache Data Engineer
Location: Hybrid (up to 3 days per week on-site, across offices in London & South England)
Contract Length: 6 Months (with scope to extend)
Start Date: ASAP
IR35: Outside
Interview Process: 1 Stage, MS Teams
Clearance Required Before Applying: SC (with eligibility for higher levels of clearance)
Our client in the public sector is hiring for an "Apache Data Engineer". The successful candidate will join a defence programme delivering a data Lakehouse architecture across AWS and 'on premises' infrastructure. The role sits within a collaborative engineering team working in agile sprints. It focuses on building secure, performant, well-labelled data pipelines from source systems into the Lakehouse.
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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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.
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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
- Design and build data pipelines and ETL processes into a Lakehouse architecture across cloud (AWS) and on premises platforms
- Implement change data capture and event-driven patterns to ingest data from source systems
- Develop data models for the pipeline layer
- Handle non-functional requirements including security, performance and metadata labelling
- Write unit and integration tests for pipeline components
- Work within a defined SDLC using Git-based CI/CD tooling
- Contribute to sprint delivery as part of an integrated development team


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Required Skills
- Experience building data pipelines within Lakehouse architectures
- Comfortable with Apache tooling, for data engineering work
- Experience with event sourcing, change data capture and event-driven architectures
- Java and/or Groovy, with a solid grasp of object-oriented design principles
- Experience working in an SDLC with an integrated team on CI/CD tooling (Git)
Nice-to-have
- Apache NiFi
- AWS, particularly EMR, S3 and SQS
- Awareness of domain-driven design
- Linux and scripting
- Postgres or PL/SQL
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