Engineer the Quantum RevolutionYour expertise can help us shape the future of quantum computing at Oxford Ionics.

View Open Roles

Data Engineer - Data Platform

eFinancialCareers
Greater London
3 weeks ago
Applications closed

Related Jobs

View all jobs

Data Engineer

Data Engineer

Data Engineer

Data Engineer

Data Engineer

Data Engineer

Our Data Services Team offers a variety of data products with a strong focus on engineering, including data science and data analytics, to help our business users, mainly trading teams, make data-driven decisions and improve their business operations.

At Macquarie, our advantage is bringing together diverse people and empowering them to shape all kinds of possibilities. We are a global financial services group operating in 31 markets and with 56 years of unbroken profitability. You'll be part of a friendly and supportive team where everyone - no matter what role - contributes ideas and drives oues.

What role will you play?

As a Data Platform Engineer, you will join our dynamic Engineering team developing cutting-edge data product solutions. You will build and maintain applications ranging from cloud infrastructure automation, APIs, query engines, and orchestration platforms. Our flat structure means that you will directly contribute to our strategy while taking ownership of a diverse range of projects utilising the latest technologies.

What you offer

A dynamic individual with a strong DevOps and Engineering background Proficient in writing infrastructure as code for public cloud Experience with Python coding/testing or any Cloud-based technology (AWS preferred) Good understanding of Data Observability Good understanding of Hosting Platform Linux/Unix (EKS and Container experience is a plus) Good understanding of Databases, Data Lakes, and Query Engines, SQL/DDLs is preferred

We love hearing from anyone inspired to build a better future with us, if you're excited about the role or working at Macquarie we encourage you to apply.

What we offer

At Macquarie, you're empowered to shape a career that's rewarding in all the ways that matter most to you. Macquarie employees can access a wide range of benefits which, depending on eligibility criteria, include: 1 wellbeing leave day per year and a minimum of 25 days of annual leave. 26 weeks' paid parental leave for primary caregivers along with 12 days of paid transition leave upon return to work and 6 weeks' paid leave for secondary caregivers Paid fertility leave for those undergoing or supporting fertility treatment 2 days of paid volunteer leave and donation matching Access to a wide range of salary sacrificing options Benefits and initiatives to support your physical, mental and financial wellbeing including,prehensive medical and life insurance cover Access to our Employee Assistance Program, a robust behavioural health network with counselling and coaching services Access to a wide range of learning and development opportunities, including reimbursement for professional membership or subscription Access topany funded emergency and backup dependent care services Recognition and service awards Hybrid and flexible working arrangements, dependent on role Reimbursement for work from home equipmentAbout Technology

Technology enables every aspect of Macquarie, for our people, our customers and ourmunities. We're a global team that is passionate about accelerating the digital enterprise, connecting people and data, building platforms and applications and designing tomorrow's technology solutions.

Ourmitment to diversity, equity and inclusion

We aremitted to providing a working environment that embraces diversity, equity, and inclusion. We encourage people from all backgrounds to apply regardless of their identity, including age, disability, neurodiversity, gender (including gender identity or expression), sexual orientation, marriage or civil partnership, pregnancy, parental status, race (including ethnic or national origin), religion or belief, or socio-economic background. We wee further discussions on how you can feel included and belong at Macquarie as you progress through our recruitment process.
Our aim is to provide reasonable adjustments to individuals as required during the recruitment process and in the course of employment. If you require additional assistance, please let us know during the application process.

Job ID 16099

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 Future of Data Science Jobs: Careers That Don’t Exist Yet

Data science has rapidly become one of the most influential disciplines of the digital age. Once a niche combination of statistics and computing, it is now central to how organisations innovate, compete, and grow. From healthcare and finance to retail, logistics, and government, data science is reshaping decision-making across every sector. In the UK, data science has grown into a core career pathway. Salaries are competitive, demand continues to rise, and roles now extend far beyond analytics into artificial intelligence, machine learning, and predictive modelling. Yet as technologies evolve, many of the most important data science careers of the future don’t exist today. This article explores why entirely new roles will emerge, the kinds of careers that may appear, how existing jobs will evolve, why the UK is well placed to lead, and what professionals can do to prepare for this transformation.

Seasonal Hiring Peaks for Data Science Jobs: The Best Months to Apply & Why

The UK's data science sector has matured into one of Europe's most intellectually rewarding and financially attractive technology markets, with roles spanning from junior data analysts to principal data scientists and heads of artificial intelligence. With data science positions commanding salaries from £30,000 for graduate data analysts to £140,000+ for senior principal scientists, understanding when organisations actively recruit can dramatically accelerate your career progression in this intellectually stimulating and rapidly evolving field. Unlike traditional analytical roles, data science hiring follows distinct patterns influenced by business intelligence cycles, research funding schedules, and machine learning project timelines. The sector's unique combination of mathematical rigour, business impact requirements, and cutting-edge technology adoption creates predictable hiring windows that strategic professionals can leverage to advance their careers in extracting insights from tomorrow's data. This comprehensive guide explores the optimal timing for data science job applications in the UK, examining how enterprise analytics strategies, academic research cycles, and artificial intelligence initiatives influence recruitment patterns, and why strategic timing can determine whether you join a pioneering AI research team or miss the opportunity to develop the next generation of intelligent systems.

Pre-Employment Checks for Data Science Jobs: DBS, References & Right-to-Work and more Explained

Pre-employment screening in data science reflects the discipline's unique position at the intersection of statistical analysis, machine learning innovation, and strategic business intelligence. Data scientists often have privileged access to comprehensive datasets, proprietary algorithms, and business-critical insights that form the foundation of organisational strategy and competitive positioning. The data science industry operates within complex regulatory frameworks spanning GDPR, sector-specific data protection requirements, and emerging AI governance regulations. Data scientists must demonstrate not only technical competence in statistical modelling and machine learning but also deep understanding of research ethics, data privacy principles, and the societal implications of algorithmic decision-making. Modern data science roles frequently involve analysing personally identifiable information, financial data, healthcare records, and sensitive business intelligence across multiple jurisdictions and regulatory frameworks simultaneously. The combination of analytical privilege, predictive capabilities, and strategic influence makes thorough candidate verification essential for maintaining compliance, security, and public trust in data-driven insights and automated systems.