UST
Data Analyst/Data Modelling Analyst(Lead II - Data Engineering)

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Role Description
Role: Data Analyst/Data Modelling Analyst
Hybrid working model with 3 days work from office
Permanent/ Fixed term/ Contract inside IR 35
Contract Length: Initial 3 months-6 months
Immediate start
Applicants must be legally authorized to work in the United Kingdom without the need for current or future visa sponsorship
Responsibilities
Data Analysis & Insight Generation
- Analyse business and operational data to identify trends, insights, risks and opportunities.
- Develop clear and actionable recommendations based on data analysis.
- Support the creation and maintenance of dashboards, reports and datasets that enable informed decision-making.
- Define, track and report on key performance indicators and success metrics.
- Work with stakeholders to understand data requirements and translate them into meaningful analytical outputs.
Data Quality & Governance
- Ensure data quality and integrity across the full data lifecycle, from source systems through to reporting and analytics.
- Conduct data validation, reconciliation and quality assurance activities to identify and resolve data issues.
- Support the definition and implementation of data quality rules and controls.
- Assist with documenting data lineage, transformations and business definitions to support transparency and trust in data.
- Promote best practices for data governance, accuracy and consistency.
Data Modelling & Architecture Support
- Support the design, development and maintenance of logical and physical data models across business domains.
- Assist with dimensional modelling activities, including fact and dimension design using Kimball methodologies.
- Support the documentation and maintenance of Data Vault models within raw and business integration layers.
- Help define and document data flows, business entities and relationships across enterprise systems.
- Contribute to the ongoing development of architecture standards, principles and modelling best practices.
- Support metadata management, data catalogue and data discoverability initiatives.
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.
Requirements & Business Engagement
- Engage with business stakeholders to understand requirements, pain points and opportunities.
- Translate business requirements into clear and technically viable data specifications.
- Collaborate with Engineers, Architects and Product teams to ensure solutions meet business needs.
- Support workshops, discovery activities and requirement gathering sessions.
- Maintain clear traceability between user requirements and delivered data products.
Collaboration & Communication
- Work closely with Data Architects, Data Engineers, Product Managers and Business stakeholders to deliver effective data solutions.
- Produce clear documentation, presentations and recommendations suitable for technical and non-technical audiences.
- Communicate findings, insights and proposed solutions in a concise and engaging manner.
- Support adoption and understanding of data products through training, documentation and stakeholder engagement
Skills & Experience
Essential
- Strong analytical skills with the ability to interpret complex datasets and translate findings into actionable insights.
- Proficiency in SQL with experience querying, validating and analysing data directly from databases.
- Experience working with reporting tools, dashboards, performance metrics and analytical datasets.
- Understanding of data quality principles, validation techniques and governance processes.
- Ability to gather and document business requirements and translate them into technical solutions.
- Strong problem-solving and critical-thinking capabilities.
- Excellent written and verbal communication skills.
- Experience using Microsoft Excel and data visualisation tools such as Power BI.
- Ability to manage multiple tasks and priorities in a fast-paced environment.


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Desirable
- Understanding of dimensional modelling techniques, including fact and dimension modelling.
- Exposure to Kimball methodology and data warehousing concepts.
- Understanding of Data Vault principles and modern data architecture practices.
- Experience documenting data lineage, metadata and business definitions.
- Familiarity with cloud-based data platforms and analytics ecosystems.
If interested, please apply with your updated CV for an immediate discussion
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- Understanding of data governance, master data and enterprise data management concepts.
- Experience working in Agile delivery environments.
- Exposure to data catalogue or metadata management tools.
- Experience using Databricks for querying, analysing and transforming data within cloud-based analytics environments.
Skills
Data Analysis, Data Modeling, Power BI, SQL, Cloud Data Warehousing, Dashboard Development, Metadata Management, Databricks, Data Vault, Data Validation, Microsoft Excel
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