Jobgether
Member of Engineering (Data & Analytics)

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Member of Engineering (Data & Analytics)
This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Member of Engineering (Data & Analytics) based in United Kingdom.
This role focuses on building the foundational data and analytics infrastructure that enables advanced AI research and development.
You will design and operate critical systems that support experimentation, model training workflows, and large-scale data analysis.
Working closely with researchers and engineers, you will help accelerate the development of next-generation intelligent systems.
The position combines software engineering, distributed systems, and data platform development in a highly innovative environment.
You will have ownership over complex technical challenges, from data modeling and ingestion to retrieval and analytics.
This is an opportunity to contribute to cutting-edge AI infrastructure while collaborating with a globally distributed team.
Accountabilities:
The Member of Engineering (Data & Analytics) will be responsible for:
- Creating reliable, scalable, and intuitive data platforms that accelerate research workflows and improve the efficiency of AI development.
- Designing, building, and operating data and analytics systems supporting advanced model development workflows.
- Owning the complete lifecycle of experiment data, including data modeling, ingestion, retrieval, querying, analysis, and retention.
- Developing high-performance data infrastructure capable of supporting increasing scale, reliability, and performance requirements.
- Collaborating closely with research teams to understand workflows and translate data needs into effective technical solutions.
- Building and maintaining distributed systems, data pipelines, and analytics platforms.
- Contributing to greenfield projects while improving and scaling existing systems.
- Driving technical initiatives by identifying opportunities, defining solutions, and collaborating across teams.
- Ensuring systems are reliable, observable, maintainable, and optimized for long-term growth.
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:
The ideal candidate has:
- Strong experience building large-scale data systems and distributed infrastructure, with the ability to solve complex technical challenges in a fast-moving environment.
- Strong programming skills in Go, Python, or similar programming languages.
- Proven experience designing, building, and operating distributed systems at scale.
- Strong understanding of distributed systems concepts, including consistency models, queue and stream processing, and data pipelines.
- Experience working with cloud infrastructure, Kubernetes, and production observability systems.
- Ability to independently lead complex and ambiguous technical initiatives while collaborating with cross-functional teams.
- Strong problem-solving skills with a focus on building scalable and reliable engineering solutions.
- Experience with OLAP databases, time-series databases, high-cardinality datasets, or large-scale analytics systems is a plus.
- Familiarity with machine learning research workflows and experimentation environments is considered an advantage.
- Excellent communication skills and the ability to work effectively in a distributed, international team.


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Benefits:
- Fully remote work environment with flexible working hours.
- 37 days per year of vacation and holidays.
- Health insurance allowance covering you and eligible dependents.
- 16 weeks of flexible, fully paid parental leave.
- Well-being, continuous learning, and home office allowances.
- Company-provided equipment.
- Regular team gatherings and opportunities for in-person collaboration.
- Inclusive, people-first culture focused on collaboration and innovation.
- Opportunity to work on impactful AI systems and contribute to cutting-edge technology development.
How Jobgether works:
We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.
We appreciate your interest and wish you the best!
Why Apply Through Jobgether?
Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.
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