Whitehall Resources
Data Engineer

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Data Engineer
Whitehall Resources are looking for a Data Engineer. This role is hybrid working with 2 days per week onsite in Cambridge, and the remainder remote working on an initial 6 month contract.
Inside IR35
Job Overview:
We are seeking an experienced Data Engineer to design and deliver scalable, high-quality data solutions in Databricks. You will play a key role in evolving our enterprise data platform, creating trusted, AI-ready data products that power reporting, analytics, automation and AI across Enterprise IT. You will design and build modern data pipelines integrating enterprise platforms such as AI platforms including Microsoft Copilot, OpenAI and other enterprise AI services. The role will also contribute to our growing AI capabilities, engineering solutions for AI usage and adoption data, Retrieval-Augmented Generation (RAG), LLM integration and AI orchestration.
Responsibilities:
- Design, build and maintain scalable ETL/ELT pipelines using Databricks, PySpark, SQL and Python.
- Design scalable data models using Data Vault principles.
- Build trusted data products using Lakehouse and Medallion Architecture principles.
- Integrate data from enterprise systems including ServiceNow, Jira, Azure DevOps and AI platforms such as Copilot and OpenAI.
- Build data pipelines for AI usage, adoption, telemetry and performance analytics.
- Design and implement RAG pipelines, including ingestion, embeddings, vector/semantic search and retrieval.
- Integrate LLMs, APIs and enterprise data to support AI applications and agents.
- Build and maintain AI orchestration workflows connecting models, data, tools and business processes.
- Implement automated data quality, testing, monitoring and validation.
- Optimise solutions for performance, scalability, reliability and cost.
- Contribute to data governance, metadata, lineage, security and documentation.
- Use Git and CI/CD to support automated and reliable deployment.
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.
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.
Required Skills and Experience:
- Minimum 4 years' data engineering experience, with strong experience in Databricks.
- Strong Python, PySpark and SQL skills.
- Experience designing scalable ETL/ELT pipelines and enterprise data models.
- Strong understanding of Data Vault, Delta Lake, Lakehouse and Medallion Architecture.
- Experience integrating enterprise systems through APIs and other data interfaces.
- Experience working with structured and unstructured data.
- Practical experience with Generative AI, RAG, embeddings, vector/semantic search and LLM integration.
- Experience with AI or workflow orchestration, connecting models, data, APIs and tools.
- Experience with automated data quality, testing and monitoring.
- Experience with Git and CI/CD and good understanding of data governance and security.


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Nice to Have Skills and Experience:
- Experience with Microsoft Copilot, OpenAI/Azure OpenAI or Microsoft Graph.
- Experience with Databricks AI capabilities, including Mosaic AI and Vector Search.
- Experience with orchestration frameworks such as LangChain, LangGraph or Semantic Kernel.
- Experience developing AI agents or agentic workflows.
- Experience with Jira, ServiceNow or Azure DevOps data.
- Knowledge of Power BI, Tableau or AI/BI.
- Familiarity with Agile delivery and iterative development.
- Strong communication and collaboration skills.
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