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

Apply Now

Market Data Engineer

Intropic
City of London
3 weeks ago
Applications closed

Related Jobs

View all jobs

Python Data Engineer - Hedgefund

Lead Data Engineer - Nottingham City

Data Engineer - Crypto Algorithm Execution

Head of Data Science Technology (Product, Engineering, Design) · London ·

Head of Data Science

Director, Data Analytics

Who We Are

At Intropic, we’re building the future of financial intelligence, where deep market expertise meets the power of AI. Founded in London’s financial centre of Canary Wharf, we exist to transform complex data into clarity, precision, and action. Our culture is shaped by truth‑seeking, velocity, and ownership, values that drive how we build, learn, and collaborate every day. We move fast, think independently, and hold ourselves to the highest standards of integrity and impact. Here, curiosity isn’t just encouraged, it’s essential. If you’re driven by challenge, inspired by innovation, and ready to amplify your intelligence alongside a team of exceptional thinkers, Intropic is where your ideas can truly compound.

Who We Look For

We’re seeking a proactive and technically adept Market Data Engineer who thrives in building robust, low‑latency systems. If you're passionate about financial markets and skilled at developing real‑time data pipelines, we’d love to meet you.

Requirements
  • Bachelor’s or Master’s degree in Computer Science, Engineering, Finance, or related field
  • Proficiency in Python plus strong familiarity with C++ or Java
  • Solid understanding of real‑time feed handling, message protocols, and distributed data architecture
  • Hands‑on experience with market data sources (e.g., Bloomberg, Refinitiv) and familiarity with cloud platforms (e.g. AWS, GCP) and technologies like Kafka
  • Skilled in building scalable data pipelines (ETL, streaming) and ensuring data quality, integrity, and performance
  • Excellent attention to detail, problem‑solving mindset, and ability to manage tight SLAs
  • Effective communicator with strong stakeholder collaboration skills
Nice to have
  • Comfortable implementing monitoring, self‑service tools, and operational dashboards
  • Experience in quant finance or working with trading and research teams
  • Background in systems performance optimization and high‑throughput data environments
What You’ll Be Doing
  • Design, develop, and maintain real‑time and historical market data pipelines from various sources
  • Ensure high data integrity and system availability while handling large‑scale data processing
  • Monitor key metrics and build tools to streamline data access and operations
  • Collaborate across product teams to align infrastructure with strategic needs
  • Deliver clean, well‑tested, and maintainable code in a fast‑paced startup environment


#J-18808-Ljbffr

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 Data Science Careers: Turning Different Thinking into a Superpower

Data science is all about turning messy, real-world information into decisions, products & insights. It sits at the crossroads of maths, coding, business & communication – which means it needs people who see patterns, ask unusual questions & challenge assumptions. That makes data science a natural fit for many neurodivergent people, including those with ADHD, autism & dyslexia. If you’re neurodivergent & thinking about a data science career, you might have heard comments like “you’re too distracted for complex analysis”, “too literal for stakeholder work” or “too disorganised for large projects”. In reality, the same traits that can make traditional environments difficult often line up beautifully with data science work. This guide is written for data science job seekers in the UK. We’ll explore: What neurodiversity means in a data science context How ADHD, autism & dyslexia strengths map to common data science roles Practical workplace adjustments you can request under UK law How to talk about your neurodivergence in applications & interviews By the end, you’ll have a clearer sense of where you might thrive in data science – & how to turn “different thinking” into a real career advantage.

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

Summary: UK data science hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise rigorous problem framing, high‑quality analytics & modelling, experiment/causality, production awareness (MLOps), governance/ethics, and measurable product or commercial impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for product/data scientists, applied ML scientists, decision scientists, econometricians, growth/marketing analysts, and ML‑adjacent data scientists supporting LLM/AI products. Who this is for: Product/decision/data scientists, applied ML scientists, econometrics & causal inference specialists, experimentation leads, analytics engineers crossing into DS, ML generalists with strong statistics, and data scientists collaborating with platform/MLOps teams in the UK.

Why Data Science Careers in the UK Are Becoming More Multidisciplinary

Data science once meant advanced statistics, machine learning models and coding in Python or R. In the UK today, it has become one of the most in-demand professions across sectors — from healthcare to finance, retail to government. But as the field matures, employers now expect more than technical modelling skills. Modern data science is multidisciplinary. It requires not just coding and algorithms, but also legal knowledge, ethical reasoning, psychological insight, linguistic clarity and human-centred design. Data scientists are expected to interpret, communicate and apply data responsibly, with awareness of law, human behaviour and accessibility. In this article, we’ll explore why data science careers in the UK are becoming more multidisciplinary, how these five disciplines intersect with data science, and what job-seekers & employers need to know to succeed in this transformed field.