At a Glance
- Tasks: Design and build large-scale data pipelines using Scala and Spark.
- Company: Join a world-leading tech organisation with a high-performing engineering team.
- Benefits: Competitive pay, hybrid working, and holiday pay included.
- Other info: Opportunity for career growth in a dynamic, innovative environment.
- Why this job: Work on complex systems that impact millions globally and enhance your skills.
- Qualifications: Experience in data engineering with Scala and Spark is essential.
We are partnering with a world-leading technology organisation seeking an experienced Senior Data Engineer to join a high-performing engineering team responsible for building and operating large-scale data platforms that support advanced machine learning and recommendation systems used by millions of users globally. This is an opportunity to work on highly complex distributed systems, developing production-grade data pipelines that power critical machine learning workflows at scale.
As a Senior Data Engineer, you will design, build and operate large-scale batch data pipelines using Scala and Apache Spark. Working alongside Machine Learning Engineers, Researchers and Platform Engineers, you will help develop the infrastructure and tooling required to process vast datasets and support the delivery of intelligent, data-driven products. This role sits at the intersection of data engineering and machine learning infrastructure, with a strong focus on performance, scalability, reliability and operational excellence.
Key Responsibilities- Design, develop and maintain large-scale Scala and Spark data pipelines.
- Build new data processing capabilities within an established engineering framework.
- Own the performance, reliability and operational excellence of data pipelines.
Senior Data Engineer - Scala/Spark employer: Morgan McKinley
Join a world-leading technology organisation that values innovation and collaboration, offering a dynamic work culture where your contributions directly impact millions of users globally. With hybrid working options and competitive pay, this role not only provides the chance to work on cutting-edge data engineering projects but also fosters professional growth through exposure to advanced machine learning systems and a supportive team environment. Embrace the opportunity to enhance your skills in a high-performing engineering team dedicated to operational excellence and scalability.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Data Engineer - Scala/Spark
✨Tip Number 1
Network like a pro! Reach out to your connections in the tech industry, especially those who work with data engineering. A friendly chat can lead to insider info about job openings or even referrals that could give you an edge.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving Scala and Spark. This gives potential employers a taste of what you can do and sets you apart from the crowd.
✨Tip Number 3
Prepare for technical interviews by brushing up on your data pipeline design and machine learning concepts. Practise coding challenges related to Scala and Spark to demonstrate your expertise during the interview.
✨Tip Number 4
Don’t forget to apply through our website! We’ve got loads of opportunities waiting for talented folks like you. Plus, it’s a great way to ensure your application gets seen by the right people.
We think you need these skills to ace Senior Data Engineer - Scala/Spark
Some tips for your application 🫡
Tailor Your CV:Make sure your CV highlights your experience with Scala and Spark. We want to see how you've tackled large-scale data pipelines before, so don’t hold back on those details!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Tell us why you're passionate about data engineering and how your skills align with our needs. Keep it engaging and relevant to the role.
Showcase Your Projects:If you've worked on any cool projects involving machine learning or data processing, make sure to mention them. We love seeing real-world applications of your skills, so share those success stories!
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for this exciting opportunity!
How to prepare for a job interview at Morgan McKinley
✨Know Your Tech Inside Out
Make sure you brush up on your Scala and Spark knowledge. Be ready to discuss your previous projects in detail, especially those involving large-scale data pipelines. We recommend preparing specific examples that showcase your problem-solving skills and how you've tackled performance and reliability challenges.
✨Understand the Company’s Data Needs
Research the technology organisation you're interviewing with. Understand their products and how they leverage data for machine learning. This will help you tailor your answers to show how your experience aligns with their goals, making it clear that you’re not just a fit for the role, but also for the company culture.
✨Prepare for Technical Questions
Expect technical questions that test your understanding of distributed systems and data engineering principles. We suggest practising coding problems related to data processing and algorithms. You might even want to do some mock interviews with friends or use online platforms to get comfortable with the format.
✨Showcase Your Collaboration Skills
Since you'll be working closely with Machine Learning Engineers and Researchers, be prepared to discuss how you’ve collaborated in the past. Share examples of how you’ve contributed to team projects and how you handle feedback. This will demonstrate your ability to work effectively in a high-performing engineering team.
