Qh4 Consulting
Data & AI Engineer - Investment Management

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Data & AI Engineer - Investment Management
Junior Data & AI Engineer – London
Location: London | Sector: Asset Management
A London-based Asset Manager is committed to expanding its technology team and is seeking a Junior Data & AI Engineer with 3–7 years' experience in data engineering and AI/ML applications.
About the Role
We are currently hiring a data-savvy engineer to:
- Design, build, and maintain data pipelines
- Develop automation solutions to enhance operational efficiency
- Drive AI-enabled capabilities and contribute to machine learning-based initiatives
- Collaborate closely with business stakeholders on data-driven projects
The role involves working across multiple platforms, ensuring high standards of data quality while pushing the boundaries of how data improves decision-making.
Key Responsibilities
- Design, implement, and optimise data pipelines in a cloud environment
- Leverage modern data platforms such as Snowflake, Microsoft Fabric, or similar
- Develop and maintain automation solutions, including ETL/ELT processes
- депутало приводить in AI/ML projects, applying algorithms to real-world business challenges
- Work with Python, Power BI, or Azure technologies to enhance insights
- Improve data quality, governance, and reporting to support strategic decisions
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.
Requirements
- 3–7 years’ experience in data engineering with a focus on data pipelines
- Strong proficiency in SQL for querying large datasets
- Exposure to cloud data platforms like Snowflake or Microsoft Fabric
- Familiarity with Power BI or Azure (advantageous but not mandatory)
- Experience with Python or another programming language for scripting/ETL
- Interest in AI applications for business problem-solving
- Ability to work across teams and streamline data-driven processes


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Ideal Traits
- Strong analytical mindset with a passion for leveraging data
- Enthusiasm for solving operational inefficiencies with engineering solutions
- Collaborative spirit for bridging technical and business needs
- Comfort working in a small, dynamic team with autonomy and impact
What We Offer
- Excellent salary & bonus aligned with experience
- Competitive benefits package
- Fast-paced environment with limited bureaucracy—a step change from entry-level positions
- Diverse challenges in asset management with long-term scope to grow expertise
Apply now, this is an opportunity to influence decisions quickly and meaningfully across a niche but rapidly evolving firm.
“It took my CV and asked me questions relevant to understanding what kind of jobs to suggest for me. Suggestions were almost perfect. Jobs were exactly what I’ve been looking for.”
Jessica, London
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