At a Glance
- Tasks: Build scalable data solutions and support critical business intelligence initiatives.
- Company: Global tech business focused on innovation and speed.
- Benefits: Flexible work schedule, competitive salary, and opportunities for professional growth.
- Other info: Collaborative environment with strong career advancement potential.
- Why this job: Join a dynamic team and make an impact with cutting-edge data technologies.
- Qualifications: Experience with AWS, Python, SQL, and data pipeline development.
The predicted salary is between 55000 - 65000 £ per year.
This global technology business has just completed a massive migration to their own platform, and now, the stage is set for scale, innovation, and speed. Products are being built at pace, technology is unlocking new capabilities, and the experiences delivered to customers worldwide are next-level.
They are looking for a Data Engineer to become an integral part of their Data Engineering Team. Working within a modern AWS environment, you will be responsible for:
- Building scalable data solutions
- Improving automation
- Supporting critical business intelligence initiatives
Your responsibilities will include:
- Designing, building, and maintaining scalable data pipelines and ETL processes
- Developing data solutions using AWS services including Glue, Lambda, S3, Redshift, and EMR
- Supporting the migration of our existing SQL Server data warehouse to AWS
- Contributing to the design and implementation of modern data lakehouse and data warehousing architectures
- Building and optimising real-time and batch data processing solutions using PySpark and related technologies
- Collaborating with Data Scientists, Analysts, and business stakeholders to deliver data-driven solutions
- Providing technical guidance and support to junior team members when required
Required skills:
- Strong hands-on experience with AWS services such as Glue, Lambda, S3, Redshift, and EMR
- Proven experience building and maintaining data pipelines and ETL frameworks
- Strong Python and SQL development skills
- Experience working with PySpark and large-scale data processing environments
- Solid understanding of data warehousing concepts and best practices
- Experience working within Agile delivery environments
- Understanding of data governance, security, and privacy best practices
Ready to join a tech team that’s building for millions?
Senior Engineer, Data Engineering employer: MRJ Recruitment
This global technology business is an exceptional employer, offering a dynamic work culture that fosters innovation and collaboration. With a strong focus on employee growth, team members benefit from hands-on experience in a modern AWS environment, alongside opportunities to work with cutting-edge technologies and contribute to impactful projects. Located in Manchester, the company promotes a healthy work-life balance with flexible working arrangements, making it an ideal place for those seeking meaningful and rewarding employment.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Engineer, Data Engineering
✨Tip Number 1
Network like a pro! Reach out to current employees on LinkedIn or attend industry meetups. We know that personal connections can give you the inside scoop on what the team is really like and might even get your foot in the door.
✨Tip Number 2
Show off your skills! Prepare a portfolio or a GitHub repository showcasing your data engineering projects. We want to see how you’ve tackled real-world problems using AWS services, Python, and SQL. It’s all about demonstrating your hands-on experience!
✨Tip Number 3
Ace the interview by being ready to discuss your past projects in detail. We recommend practising common technical questions and scenarios related to data pipelines and ETL processes. The more prepared you are, the more confident you’ll feel!
✨Tip Number 4
Don’t forget to apply through our website! We’ve got the latest job openings and applying directly can sometimes give you an edge. Plus, we’re here to support you every step of the way in landing that dream role!
We think you need these skills to ace Senior Engineer, Data Engineering
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the role of Senior Engineer, Data Engineering. Highlight your experience with AWS services like Glue and Redshift, and don’t forget to showcase your Python and SQL skills. We want to see how your background aligns with what we’re looking for!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you’re excited about this role and how your skills can contribute to our Data Engineering Team. Be genuine and let your personality come through – we love to see enthusiasm!
Showcase Relevant Projects:If you've worked on any projects that involved building data pipelines or using PySpark, make sure to mention them! We’re keen to see real-world examples of your work, especially those that demonstrate your ability to innovate and scale solutions.
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 the role. Plus, it gives you a chance to explore more about our company culture and values!
How to prepare for a job interview at MRJ Recruitment
✨Know Your Tech Stack
Make sure you’re well-versed in the AWS services mentioned in the job description, like Glue, Lambda, S3, Redshift, and EMR. Brush up on your Python and SQL skills too, as they’ll likely ask you to demonstrate your knowledge during the interview.
✨Showcase Your Projects
Prepare to discuss specific projects where you've built scalable data pipelines or worked with ETL processes. Highlight your experience with PySpark and any large-scale data processing environments to show you can hit the ground running.
✨Understand Their Business
Research the company’s recent migration to their own platform and how it impacts their data engineering needs. Being able to discuss how you can contribute to their goals will set you apart from other candidates.
✨Be Ready for Collaboration Questions
Since the role involves working with Data Scientists, Analysts, and business stakeholders, be prepared to talk about your experience in collaborative environments. Share examples of how you’ve provided technical guidance to junior team members or worked within Agile teams.
