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Orgvue
Orgvue is an organizational design and planning platform that empowers businesses to transform their workforce by understanding the work people do and the skills they have. Our platform connects strategy to structure, providing clarity of vision, so leaders can build a more adaptable, better performing organization that thrives in a constantly changing world of work.
The world's largest and best-known enterprises and consulting firms use Orgvue to visualize and model current and future states of the organization and make faster, more informed decisions. The company is headquartered in London, with offices in Philadelphia, The Hague, Toronto, and Sydney.
Role Overview
The Data & Insight Engineer will build and own an AI-native analytics environment where insights are generated automatically from data rather than manually through dashboards and reports.
This role combines data engineering, analytics engineering, and AI-enabled insight generation. Responsibilities include building semantic data models, developing automated insight pipelines, and integrating Snowflake Cortex capabilities to support conversational analytics and AI-driven business intelligence.
We are seeking a senior individual contributor who can take ownership of the analytics and AI technology stack, operate independently, and act as a trusted partner to stakeholders across the business. This is not a people management role; instead, it requires someone who enjoys balancing hands-on technical delivery with collaboration, influencing, and guiding others. The ideal candidate will be equally comfortable writing code, solving complex technical challenges, and engaging with colleagues to understand business needs and drive impactful outcomes.
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.
See breakdownIt searches the market for you
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.
Responsibilities:
Data Pipeline Engineering
- Build and maintain robust data ingestion and transformation pipelines
- Integrate data from operational systems into the analytics platform
- Maintain data quality frameworks and validation checks
- Optimise performance of data processing and analytics workloads
AI Insight Pipeline Development and Ownership
- Automate recurring analysis traditionally performed manually
- Enable natural-language analytics across curated datasets
- Develop systems that translate business questions into structured data queries
Semantic Data Modelling
- Design and maintain curated business data models that support reliable analytics and AI-driven insights
- Define core business entities, metrics, and KPI definitions
- Build and maintain semantic layers within Snowflake
Governance and Quality Assurance
- Monitor model performance, accuracy, and cost usage
- Implement safeguards to ensure reliable and explainable outputs
- Maintain governance standards for AI-enabled analytics workflows


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Requirements
- Strong SQL and data modelling expertise
- Experience working with Snowflake
- Experience with analytics engineering tools such as dbt
- Proficiency with Python or similar languages for data workflows
- Experience building and maintaining data pipelines
- Experience translating business questions into analytical models and metrics
- Experience working with analysts, product teams, and business stakeholders to support decision-making
Preferred But Not Essential
- Experience working with large language models (LLMs) or AI-enabled analytics platforms
- Familiarity with prompt design or AI-assisted analytical workflows
- Familiarity with Snowflake Intelligence
Benefits
- Hybrid working - 2 days a week in the London office
- Wellbeing: Sanctus Coaching, Virtual fitness sessions, Wellbeing webinars, Annual Wellbeing day
- Subsidised Gym Membership
- Private Medical Insurance (including Dental and Vision) and Life Assurance
- 25 days holiday (increasing to 30 days at a rate of 1 extra day per year)
- Employer pension contribution of 5% of your gross salary, if you contribute a minimum of 3%
- Season ticket Loan
- Cycle to Work Scheme
- Annual Discretionary Bonus
Here at Orgvue we promote individualism and a diverse workforce to build on our future success.
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Jessica, London
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