Adria Solutions Ltd
Data Engineering Lead – AWS & AI - Manchester

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Data Engineering Lead – AWS & AI - Manchester
An established financial services organisation is looking for a hands-on Data Engineering Lead to take ownership of its existing data estate and deliver a modern platform supporting Business Intelligence, Data Science and Applied AI.
This is an influential position combining technical leadership, platform ownership and line management. You’ll modernise the organisation’s data capabilities, introduce scalable batch and real-time processing, and eliminate manual or fragile processes through intelligent automation.
You’ll lead a small team of Data Engineers while remaining closely involved in architecture, technology selection and engineering delivery.
What you’ll be doing
- Own the reliability, security and evolution of the organisation’s data platform.
- Modernise an existing SQL Server, SSIS/SSDT and Power BI environment.
- Develop scalable batch and real-time data-processing capabilities.
- Lead the design of a Customer Data Platform.
- Build and evolve a modern AWS lakehouse architecture.
- Create governed semantic models, consistent metrics and clear data definitions.
- Enable secure, self-service data analysis through modern AI tools.
- Automate manual, repetitive and fragile data processes.
- Support BI, Data Science, Machine Learning and Applied AI teams through a unified platform.
- Own data governance, platform security, monitoring and operating costs.
- Manage, develop and help grow the Data Engineering team.
- Work closely with technical leaders and senior stakeholders across the organisation.
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.
What we’re looking for
You’ll be an experienced Data Engineer or Data Engineering Lead who has built and operated complete data platforms—not simply individual components.
You’ll combine strong technical knowledge with the confidence to make architectural decisions, lead change and determine when existing technology should be evolved or replaced.
Your experience should include:
- Batch processing, data warehousing, ELT and orchestration.
- Modern streaming technologies such as Flink or comparable platforms.
- Production AWS data engineering.
- AWS services including S3, Lambda, Glue, Athena, Kinesis, RDS, IAM and CloudWatch.
- Lakehouse architectures and open table formats such as Iceberg.
- Medallion-style data layering and dimensional modelling.
- Strong SQL and Python development skills.
- Infrastructure as code using Terraform.
- CI/CD, automated testing and modern engineering practices.
- SQL Server, SSIS/SSDT and Power BI.
- Semantic models, shared metrics and data glossaries.
- Data governance, retention, lineage, classification and auditability.
- Managing, mentoring or developing Data Engineers.


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You should also be comfortable using advanced AI coding assistants, such as Claude Code or equivalent tools, to accelerate development across code, infrastructure, testing and documentation while maintaining appropriate quality and security controls.
Desirable experience
- Financial services or another regulated environment.
- PySpark for large-scale batch or streaming transformations.
- Migrating SQL Server and SSIS estates to lakehouse or metadata-driven architectures.
- Customer Data Platforms or event-driven systems.
- Data-quality tools such as dbt tests or Great Expectations.
- MCP servers or governed natural-language data interfaces.
- Financial crime, fraud or regulatory-reporting data.
- Power BI administration and semantic modelling.
Why apply?
This is an opportunity to take genuine ownership of a business-critical data platform and shape how data and AI are used across an organisation.
You’ll have the freedom to introduce modern technologies, develop a talented engineering team and build a platform capable of supporting future analytics, AI products and strategic decision-making.
Location: Manchester
Working pattern: Hybrid
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