Deloitte
AI Data Engineer (Azure)

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Job Title: AI Data Engineer (Azure)
Location: London Hybrid. Travel to the London office 2 days a week
Duration: 6 months
Contract Start Date: ASAP
Day rate: Competitive (Inside IR35)
About Deloitte
Working with the Deloitte Associate (Contractor) Programme means we can offer you the opportunity to work on a variation of industry and client-related projects. Our aim is to retain the best talent and so when your project end date nears our team of Talent Community Advisors will be working with you to look at alternative projects within the firm that suit your experience should you wish to continue with Deloitte.
The Role
We are looking for a highly skilled AI Data Engineer (Contractor) specialising in Azure to join our Digital Innovation team, supporting cutting-edge data and analytics use cases across Tax & Legal. This role is ideal for someone who combines strong AI/GenAI data pipeline expertise with hands-on Azure, data discovery and analysis. You will be comfortable working with unstructured data and modern Azure-native architectures. You will play a key role in transforming complex datasets into meaningful insights, working closely with Tax domain specialists to understand requirements, shape solutions, and clearly present outputs that drive business value. We're looking for a strong communicator with problem-solving skills who can bridge technical data engineering and business understanding. A proactive, delivery-focused engineer who is comfortable working at pace.
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.
Deliverables
- Data Engineering & Azure Platform Delivery
- Design and build end-to-end data pipelines using Azure (ADF, Synapse, Fabric)
- Develop scalable frameworks for ingesting structured, semi-structured, and unstructured data
- Implement modern architectures (e.g. Lakehouse, medallion – bronze/silver/gold)
- Build and optimise storage solutions across ADLS Gen2, Cosmos DB, and Azure SQL/Synapse
- Deliver scalable, maintainable, production-ready solutions
- Unstructured Data & NoSQL Engineering
- Design pipelines to process, transform, and enrich unstructured data.
- Leverage Cosmos DB for high-throughput, low-latency, schema-flexible workloads
- Optimise partitioning, indexing, and query performance
- Enable downstream analytics and AI use cases (e.g. reporting, search, RAG)
- Data Discovery, Analysis & Business Engagement
- Conduct data discovery, profiling, and exploratory analysis
- Collaborate with Tax & Legal stakeholders to translate business needs into data solutions
- Identify trends, anomalies, and data quality issues
- Present insights clearly to non-technical and senior stakeholders
- Support development of curated datasets and semantic layers
- Collaboration & Delivery
- Work with data scientists, AI engineers, architects, and domain specialists
- Enable data consumption via reporting tools, APIs, and data services
- Contribute to best practices in governance, lineage, and data cataloguing
- Deliver high-quality solutions in agile environments


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Essential Skills and Experience
- Proven experience as an Azure Data Engineer in end-to-end data platforms
- Exposure to AI/GenAI data pipelines (e.g. RAG, embeddings, search)
- Knowledge of Azure AI Search or vector-based retrieval systems
- Strong hands-on experience with: Azure Data Factory / Synapse / Microsoft Fabric, Azure Data Lake Storage (ADLS Gen2), Azure Cosmos DB (Core/SQL API, NoSQL modelling)
- Experience working extensively with unstructured and semi-structured data
- Proficiency in Python and SQL
- Experience building scalable, production-grade data pipelines
- Familiarity with CI/CD and DevOps practices in Azure
- Demonstrated experience in:
- Data discovery, profiling, and exploratory analysis
- Data transformation and data quality frameworks
- Strong understanding of:
- NoSQL vs relational data modelling
- Data partitioning and performance tuning
Desirable
- Azure Data Engineering Associate certification (DP-203) or equivalent
- Experience with Microsoft Fabric and Lakehouse architectures
- Experience integrating Cosmos DB with analytical platforms
- Familiarity with data governance frameworks
IR35
As a means of managing tax, commercial and reputational risks, Deloitte prohibits the use of Associates through Personal Service Companies (‘PSCs’). All Associates must contract under PAYE arrangements through a Deloitte approved ‘Employment Company’ (aka ‘umbrella company’).
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