At a Glance
- Tasks: Join our team to develop innovative data solutions and automate cloud infrastructure.
- Company: Macquarie Group, a global financial services leader with a supportive culture.
- Benefits: Enjoy flexible working, generous leave, and wellness support.
- Other info: Diverse and inclusive workplace with excellent career growth opportunities.
- Why this job: Make a real impact in a dynamic environment using cutting-edge technology.
- Qualifications: Experience in DevOps, Python, and cloud technologies like AWS.
The predicted salary is between 60750 - 74250 £ per year.
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, to 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 outcomes.
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 (AWS), 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 who loves to solve problems and build automation and CI/CD Pipelines in the data space and cloud infrastructure.
- Proficient in writing infrastructure as code for public cloud.
- Experience with Python coding/testing or any Cloud-based technology (AWS preferred).
- 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
- Hybrid and flexible working arrangements.
- One wellbeing leave day per year and a minimum of 25 days of annual leave.
- Primary carers are eligible for a minimum of 20 weeks paid leave and a minimum of 6 weeks for secondary carer.
- Paid volunteer leave and donation matching.
- Range of benefits to support your physical, psychological, and financial wellbeing.
- Employee Assistance Program, a robust behavioural health network with counselling and coaching services.
- Recognition and service awards.
About Technology
Technology enables every aspect of Macquarie, for our people, our customers, and our communities. 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.
Our commitment to diversity, equity, and inclusion
We are committed 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 welcome 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.
Data Engineer, Data Platform in London employer: Macquarie Group
Macquarie Group is an exceptional employer, offering a dynamic work culture in the heart of London that fosters innovation and collaboration. Employees benefit from comprehensive growth opportunities, including leadership development and exposure to senior stakeholders, all while contributing to impactful capital strategy initiatives that drive the organisation's success. With a commitment to employee well-being and a supportive team environment, Macquarie Group stands out as a rewarding place to advance your career.
StudySmarter Expert Advice🤫
We think this is how you could land Data Engineer, Data Platform in London
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We think you need these skills to ace Data Engineer, Data Platform in London
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
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Craft a Tailored Cover Letter:For a full-time role at Macquarie Group, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Macquarie Group. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Macquarie Group
✨Brush Up on Your Statistics
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✨Get Comfortable with Python and R
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✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
