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

Apply Now

HR Analytics & Data Engineer

Qube Research & Technologies
London
4 weeks ago
Applications closed

Related Jobs

View all jobs

Analytical Data Engineer

Data Engineer

Data Analyst (Software Systems Test)

HR Data Analyst

Technical Data Engineer

Qube Research & Technologies (QRT) is a global quantitative and systematic investment manager, operating in all liquid asset classes across the world. We are a technology and data driven group implementing a scientific approach to investing. Combining data, research, technology, and trading expertise has shaped QRT's collaborative mindset which enables us to solve the most complex challenges. QRT's culture of innovation continuously drives our ambition to deliver high quality returns for our investors.

Your future role within QRT:

As an Analytics Engineer in the HR Technology team, you will play a critical role in building and maintaining data infrastructure to support HR insights and analytics. You will focus on transforming raw data into structured formats, ensuring data is clean, accessible, and ready for use - bridging the gap between technical and business teams. You will collaborate with multiple business areas to deliver high quality data-driven analytics that empower managers, business partners and senior leaders in their roles.

  • Build and maintain scalable, secure data pipelines across platforms using AWS tools like S3, RDS and Redshift.
  • Ensure accuracy through regular testing, monitoring, and troubleshooting to enable smooth data flow.
  • Centralise data from sources like Workday and Greenhouse into warehouses for BI tools
  • Use Python and other tools to automate and optimise data workflows for seamless operations.
  • Partner with HR, analytics engineers, and leadership to deliver actionable insights, ensuring alignment between technical capabilities and business requirements.
  • Support interactive BI dashboards (e.g. Python Dash, PowerBI, Tableau etc) that empower data-driven decisions.
  • Create documentation and set documentation standards for data assets & products: ETL documentation, metric glossary.
  • Uphold data security and compliance with best practices for access control.
  • Document data pipelines, models, and transformations to support transparency, reproducibility, and scalability.

Your present skillset:

  • 3-5 years of relevant experience developing data-driven applications, ideally related to Talent/HR Analytics.
  • Strong proficiency in Python for building data pipelines, writing automation scripts and handling large datasets.
  • Experience with cloud platforms, especially AWS (S3, RDS, Redshift) for building data storage and processing solutions.
  • Experience using ETL tools to build and automate scalable data workflows.
  • Strong understanding of data modelling concepts, metrics and semantic layers and their application in BI environments.
  • Experience working with HR data and platforms like Workday, as well as an understanding of HR metrics and KPIs (e.g., retention, engagement, performance) is a plus!
  • Some front-end skills in JavaScript, HTML, CSS, with experience using libraries like React, Bootstrap, or similar

QRT is an equal opportunity employer. We welcome diversity as essential to our success. QRT empowers employees to work openly and respectfully to achieve collective success. In addition to professional achievement, we are offering initiatives and programs to enable employees achieve a healthy work-life balance.
#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.

The Best Free Tools & Platforms to Practise Machine Learning Skills in 2025/26

Machine learning (ML) has become one of the most in-demand career paths in technology. From predicting customer behaviour in retail to detecting fraud in banking and enabling medical breakthroughs in healthcare, ML is transforming industries across the UK and beyond. But here’s the truth: employers don’t just want candidates who have read about machine learning in textbooks. They want evidence that you can actually build, train, and deploy models. That means practising with real tools, working with real datasets, and solving real problems. The good news is that you don’t need to pay for expensive software or courses to get started. A wide range of free, open-source tools and platforms allow you to learn machine learning skills hands-on. Whether you’re a beginner or preparing for advanced roles, you can practise everything from simple linear regression to deploying deep learning models — at no cost. In this guide, we’ll explore the best free tools and platforms to practise machine learning skills in 2025, and how to use them effectively to build a portfolio that UK employers will notice.

Top 10 Skills in Machine Learning According to LinkedIn & Indeed Job Postings

Machine learning (ML) is at the forefront of innovation, powering systems in finance, healthcare, retail, logistics, and beyond in the UK. As organisations leverage ML for predictive analytics, automation, and intelligent systems, demand for skilled practitioners continues to grow. So, which skills are most in demand? Drawing on insights from LinkedIn and Indeed, this article outlines the Top 10 machine learning skills UK employers are looking for in 2025. You'll learn how to demonstrate these capabilities through your CV, interviews, and real-world projects.

The Future of Machine Learning Jobs: Careers That Don’t Exist Yet

Machine learning (ML) has become one of the most powerful forces reshaping the modern world. From voice assistants and recommendation engines to fraud detection and medical imaging, it underpins countless applications. ML is no longer confined to research labs—it powers business models, public services, and consumer technologies across the globe. In the UK, demand for machine learning professionals has risen dramatically. Organisations in finance, retail, healthcare, and defence are embedding ML into their operations. Start-ups in Cambridge, London, and Edinburgh are pioneering innovations, while government-backed initiatives aim to position the UK as a global AI leader. Salaries for ML engineers and researchers are among the highest in the tech sector. Yet despite its current importance, machine learning is only at the beginning of its journey. Advances in generative AI, quantum computing, robotics, and ethical governance will reshape the profession. Many of the most vital machine learning jobs of the next two decades don’t exist today. This article explores why new careers will emerge, the roles likely to appear, how today’s roles will evolve, why the UK is well positioned, and how professionals can prepare now.