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Hyqoo

Data Engineer AI

London
Posted about 14 hours ago
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Role: AI Data Engineer (agentic AI)

YOE: 6+ Years (not leading exp, only hands on Engineering exp)
Duration: 18 months
Hybrid model

We are seeking an AI Data Engineer to design, build, and optimize scalable data solutions that support advanced analytics, AI, and experimentation initiatives. You will work closely with clients and technical teams to understand data requirements, develop robust data pipelines, and transform complex datasets into reliable, analysis-ready assets.

Key Responsibilities

  • Design and develop scalable data solutions and pipelines for AI, machine learning, and advanced analytics.
  • Clean, transform, aggregate, and integrate large and complex datasets from multiple sources.
  • Design, configure, and maintain database and big-data systems.
  • Develop complex SQL queries for data extraction, transformation, validation, and analysis.
  • Build and optimize distributed data processing solutions that can scale across multiple machines.
  • Implement data quality, reliability, scalability, and disaster-recovery processes.
  • Collaborate with data scientists, engineers, analysts, and clients to support AI and advanced analytics initiatives.
  • Evaluate and leverage modern big-data and machine-learning technologies to solve complex business problems.

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.

Start with a chat, not a search bar

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.

P

Graduate Consultant — 2026 Scheme

PwC·London, UK
£35,000/yr

Why you're a good match

Strong

Your 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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It 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.

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Strong

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.

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Strong

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.

Required Qualifications & Skills

  • Advanced degree in Computer Science, Data Engineering, or a related field, or equivalent practical experience.
  • Hands-on experience building data engineering solutions for AI, machine learning, or advanced analytics.
  • Strong knowledge of big-data technologies, including Hadoop and Spark.
  • Strong programming skills in Python, Java, SQL, and/or Scala.
  • Experience with data processing, ETL/ELT, data transformation, and large-scale data environments.
  • Familiarity with advanced analytics and machine-learning tools such as Anaconda, Spark MLlib, or similar technologies.
  • Understanding of distributed computing, database architecture, and scalable data platforms.
  • Strong analytical and problem-solving skills.

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Soft Skills

  • Excellent communication and collaboration skills, with the ability to work effectively with both technical teams and clients.
  • Strong intellectual curiosity and a willingness to learn and work across new technologies and problem domains.
  • Ability to operate effectively in a fast-paced environment and take ownership of complex data challenges.
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Location

London, England, United Kingdom

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