iXceed Solutions
Data Engineer

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Role: Data Engineer
Location: Sheffield, UK (Hybrid 3 days onsite/week)
Job Type: Sub-con
Job description
Principal accountabilities and responsibilities
- Lead technical delivery of data foundations for Operational Resilience providing a governed reusable data layer that underpins how the bank measures resilience maps service dependencies and tests scenario assumptions across Procurement and Real Estate Services
- Design, build, and operate robust data pipelines across the data lifecycle (i.e., sourcing, ingestion, transformation, modelling, and publishing data assets)
- Build, deploy, and maintain Data Products aligned to common patterns, standards, including clear data contracts, quality rules, documentation, and operational runbooks
- Partner with Data Architects and Technology teams to implement solutions that meet architecture standards, technology controls, and non-functional requirements (performance, recoverability, auditability)
- Implement data quality, lineage, and governance requirements, support metadata capture and stewardship activities (e.g., using tooling such as Collibra)
- Build data models (conceptual, logical, physical) as appropriate to enable consistent KPIs, dashboards, and regulatory management reporting outcomes
- Contribute to platform adoption by shaping and delivering datasets and data products optimised for the CxO Strategic Data Platform and Data Fabric publishing patterns
- Own technical delivery for relevant Data Products, manage backlog, define acceptance criteria, prioritise enhancements, and coordinate delivery with engineers, analysts, and business stakeholders
- Identify and manage delivery risks, operational risks, and process blockers; ensure clear status reporting and dependency management across the programme
- Produce clear documentation, roadmaps, data dictionaries, architecture diagrams, operating procedures in Confluence, and maintain delivery traceability in JIRA
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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Every day your agent scans the market matching roles against what actually matters to you, not just keywords on a CV.
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.
Skills/experience required
- Strong understanding of Operational Resilience concepts and hands-on experience with relevant data (e.g., service impact tolerances, asset dependency, incidents, outages, DR, BCP test evidence, concentration indicators)
- Conceptual understanding of Procurement, Real Estate, and associated data domains preferred
- Demonstrable understanding of graph concepts (nodes, edges, typed relationships, multihop traversal, path analysis) and ability to apply in the context of Operational Resilience (e.g., what-if analysis, identifying critical path, single point of failure)
- Demonstrable experience in a data engineering role delivering end-to-end data solutions, data sourcing, ingestion, data warehouse, refinery patterns, data asset delivery
- Strong SQL skills and experience with relational data modelling and optimisation
- Hands-on experience with cloud data tooling and services (e.g., Google Cloud Platform, including BigQuery, or equivalent)
- Strong coding capability in Python with solid software engineering practices, version control, testing, CI/CD where applicable
- Experience with enterprise data technologies and platforms commonly used in large organisations and data integration patterns
- Experience with data governance and operating discipline, metadata lineage, access controls, retention, and data standards
- Experience with Agile delivery and familiarity with relevant tools (JIRA and Confluence)
- Strong written and verbal communication skills, including the ability to work effectively with technical and non-technical stakeholders


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Soft skills required
- Structured thinking and problem-solving; able to break complex problems into deliverable increments and make clear tradeoffs
- Ability to work independently, taking clear ownership of outcomes and managing timely delivery
- Collaborative ways of working in cross-functional, geographically dispersed teams
- Effective stakeholder management across business, technology, operations, and risk partners
- Proactive continuous-improvement mindset; spots opportunities to simplify, standardise, and scale
Mandatory Skills:
- CI/CD Architecture
- GCP BigQuery
- Python
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