Data Engineer - £115,000 - Snowflake - London - Hybrid

City of London
11 months ago
Applications closed

Related Jobs

View all jobs

Data Engineer (Data Science)

Data Engineer (Data Science)

Senior DataOps Engineer

Machine Learning Engineer

Data Science & ML Engineer (Azure Data Pipelines)

Data/Machine Learning Ops Engineer

Data Engineer - £115,000 - Snowflake - London - Hybrid

Company Overview:

My client is a leading global commodities merchant and infrastructure asset investor, specialising in the physical and financial trading of energy commodities. They leverage advanced data analytics and cutting-edge technology to optimise trading strategies and asset management. With a strong focus on data-driven decision-making, they provide innovative solutions in data engineering, analytics, and technology integration.

Role Overview:

As a Data Engineer, you will be crucial in developing a top-tier data science platform integral to my clients investment strategy. Your role involves implementing new data management platforms, creating data ingestion pipelines, and sourcing new data sets. You will handle all aspects of data, from architecture design to ongoing management, and work closely with Risk and commercial investing teams globally.

Requirements:

Exceptional Data Engineering skills and experience
Advanced Python and SQL skills
Experience with Data Architecture and Dimensional Modelling
Hands-on experience with SnowflakeNice to Have:

ML / AI Experience
SnapLogic

Interviews ongoing don't miss your chance to secure this life changing role!

Contact me @ (url removed) or on (phone number removed).

MySQL, Python, Snowflake, Data Engineer, Commodities, Oracle, ETL, Data Science, AI

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.

Maths for AI Jobs: The Only Topics You Actually Need (& How to Learn Them)

If you are a software engineer, data scientist or analyst looking to move into AI or you are a UK undergraduate or postgraduate in computer science, maths, engineering or a related subject applying for AI roles, the maths can feel like the biggest barrier. Job descriptions say “strong maths” or “solid fundamentals” but rarely spell out what that means day to day. The good news is you do not need a full maths degree worth of theory to start applying. For most UK roles like Machine Learning Engineer, AI Engineer, Data Scientist, Applied Scientist, NLP Engineer or Computer Vision Engineer, the maths you actually use again & again is concentrated in a handful of topics: Linear algebra essentials Probability & statistics for uncertainty & evaluation Calculus essentials for gradients & backprop Optimisation basics for training & tuning A small amount of discrete maths for practical reasoning This guide turns vague requirements into a clear checklist, a 6-week learning plan & portfolio projects that prove you can translate maths into working code.

Neurodiversity in AI Careers: Turning Different Thinking into a Superpower

The AI industry moves quickly, breaks rules & rewards people who see the world differently. That makes it a natural home for many neurodivergent people – including those with ADHD, autism & dyslexia. If you’re neurodivergent & considering a career in artificial intelligence, you might have been told your brain is “too much”, “too scattered” or “too different” for a technical field. In reality, many of the strengths that come with ADHD, autism & dyslexia map beautifully onto AI work – from spotting patterns in data to creative problem-solving & deep focus. This guide is written for AI job seekers in the UK. We’ll explore: What neurodiversity means in an AI context How ADHD, autism & dyslexia strengths match specific AI roles Practical workplace adjustments you can ask for under UK law How to talk about your neurodivergence during applications & interviews By the end, you’ll have a clearer picture of where you might thrive in AI – & how to set yourself up for success.

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

As we head into 2026, the AI hiring market in the UK is going through one of its biggest shake-ups yet. Economic conditions are still tight, some employers are cutting headcount, & AI itself is automating whole chunks of work. At the same time, demand for strong AI talent is still rising, salaries for in-demand skills remain high, & new roles are emerging around AI safety, governance & automation. Whether you are an AI job seeker planning your next move or a recruiter trying to build teams in a volatile market, understanding the key AI hiring trends for 2026 will help you stay ahead. This guide breaks down the most important trends to watch, what they mean in practice, & how to adapt – with practical actions for both candidates & hiring teams.