Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Data Production Engineer

Farringdon Without
7 months ago
Applications closed

Related Jobs

View all jobs

Data Engineer – AWS | Hybrid | Meaningful Projects Across Multiple Sectors

Consultant AWS Data Engineer IRC281939

Consultant Aws Data Engineer Irc281939

Data Engineer

Head of Data Engineering

Data Engineer – GCP/DSS

Data Production Engineer
Location: London, United Kingdom
Salary: Competitive + Excellent Benefits

Our client, a leading global trading firm, is seeking a talented Data Production Engineer to join their highly collaborative Data team. Data is central to their success, powering one of the world's largest and most advanced automated trading operations.

This role offers the unique opportunity to work directly with live trading teams, automate processes, explore vast datasets, and engage with key external stakeholders such as data vendors, brokers, and exchanges. You'll play a hands-on role in acquiring, validating, and preparing data that feeds cutting-edge quantitative research and real-time trading strategies.

Key Responsibilities

Data Engineering: Develop tools to onboard, classify, and reconcile data. Automate workflows using a modern Python data stack.

Data Analysis: Clean, validate, and enrich datasets; conduct in-depth reconciliations and support researchers in data exploration and feature creation.

Data Debugging: Trace anomalies to their source through a combination of technical analysis, problem-solving, and stakeholder communication.

Production Support: Monitor data pipelines, resolve issues quickly, and provide reliable support to internal users across trading and research.

About You

You're detail-oriented, curious, and thrive on solving complex data challenges.

Comfortable operating in a fast-paced, production environment.

You collaborate well with both technical and non-technical stakeholders.

Requirements

2+ years in a data engineering or data science role, or a relevant degree in a related field.

Strong Python skills are a must; familiarity with modern data tools and libraries.

Proficient in at least one SQL dialect (PostgreSQL, MySQL, MSSQL).

Comfortable using the Linux command line for file manipulation, automation, and system monitoring.

Experience with financial datasets (e.g. Refinitiv, S&P, Bloomberg) and ETL pipeline management is highly desirable.

Prior exposure to supporting systems in a production trading environment is a strong advantage.

Why Apply?

You'll join a high-impact team at the core of a global trading powerhouse, surrounded by smart, driven colleagues in an environment that prizes collaboration, innovation, and technical excellence. The culture is open, inclusive, and values ideas from all corners of the organisation.

Randstad Technologies Ltd is a leading specialist recruitment business for the IT & Engineering industries. Please note that due to a high level of applications, we can only respond to applicants whose skills & qualifications are suitable for this position. No terminology in this advert is intended to discriminate against any of the protected characteristics that fall under the Equality Act 2010. For the purposes of the Conduct Regulations 2003, when advertising permanent vacancies we are acting as an Employment Agency, and when advertising temporary/contract vacancies we are acting as an Employment Business

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Neurodiversity in Machine Learning Careers: Turning Different Thinking into a Superpower

Machine learning is about more than just models & metrics. It’s about spotting patterns others miss, asking better questions, challenging assumptions & building systems that work reliably in the real world. That makes it a natural home for many neurodivergent people. If you live with ADHD, autism or dyslexia, you may have been told your brain is “too distracted”, “too literal” or “too disorganised” for a technical career. In reality, many of the traits that can make school or traditional offices hard are exactly the traits that make for excellent ML engineers, applied scientists & MLOps specialists. This guide is written for neurodivergent ML job seekers in the UK. We’ll explore: What neurodiversity means in a machine learning context How ADHD, autism & dyslexia strengths map to ML roles Practical workplace adjustments you can ask for under UK law How to talk about neurodivergence in applications & interviews By the end, you’ll have a clearer sense of where you might thrive in ML – & how to turn “different thinking” into a genuine career advantage.

Machine Learning Hiring Trends 2026: What to Watch Out For (For Job Seekers & Recruiters)

As we move into 2026, the machine learning jobs market in the UK is going through another big shift. Foundation models and generative AI are everywhere, companies are under pressure to show real ROI from AI, and cloud costs are being scrutinised like never before. Some organisations are slowing hiring or merging teams. Others are doubling down on machine learning, MLOps and AI platform engineering to stay competitive. The end result? Fewer fluffy “AI” roles, more focused machine learning roles with clear ownership and expectations. Whether you are a machine learning job seeker planning your next move, or a recruiter trying to build ML teams, understanding the key machine learning hiring trends for 2026 will help you stay ahead.

Machine Learning Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK machine learning hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise shipped ML/LLM features, robust evaluation, observability, safety/governance, cost control and measurable business impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for ML engineers, applied scientists, LLM application engineers, ML platform/MLOps engineers and AI product managers. Who this is for: ML engineers, applied ML/LLM engineers, LLM/retrieval engineers, ML platform/MLOps/SRE, data scientists transitioning to production ML, AI product managers & tech‑lead candidates targeting roles in the UK.