At a Glance
- Tasks: Design and develop scalable data pipelines using Python and Apache Spark.
- Company: Join Deepstreamtech, a leader in innovative data solutions.
- Benefits: Competitive salary, flexible working hours, and opportunities for professional growth.
- Other info: Collaborative team culture with exciting projects and career advancement.
- Why this job: Shape the future of data platforms in a modern AWS environment.
- Qualifications: Proficient in Python with a passion for data engineering and financial analytics.
The predicted salary is between 70000 - 90000 € per year.
Deepstreamtech is seeking a Lead Software Data Engineer in Greater London to design and develop scalable data pipelines using Python and Apache Spark. You will work in a modern AWS environment to build robust data solutions and collaborate with various teams to deliver high-quality data services.
Ideal candidates should be proficient in Python, have experience with data engineering concepts, and be eager to learn about financial analytics and indices.
Join us to shape the next-generation data platform at FTSE Russell.
Lead AWS Data Engineer – Spark, ETL & Lakehouse employer: Deepstreamtech
Deepstreamtech is an exceptional employer that fosters a collaborative and innovative work culture in the heart of Greater London. With a strong focus on employee growth, we offer continuous learning opportunities and the chance to work with cutting-edge technologies in a supportive environment. Join us to not only advance your career but also contribute to shaping the future of data solutions at FTSE Russell.
StudySmarter Expert Advice🤫
We think this is how you could land Lead AWS Data Engineer – Spark, ETL & Lakehouse
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect with people on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving Python, Apache Spark, and AWS. This will give potential employers a taste of what you can do and set you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and soft skills. Practice common data engineering questions and be ready to discuss your experience with ETL processes and data pipelines.
✨Tip Number 4
Don’t forget to apply through our website! We’re always on the lookout for talented individuals like you. Keep an eye on our job listings and make sure your application stands out!
We think you need these skills to ace Lead AWS Data Engineer – Spark, ETL & Lakehouse
Some tips for your application 🫡
Tailor Your CV:Make sure your CV highlights your experience with Python, Apache Spark, and data engineering concepts. We want to see how your skills align with the role, so don’t be shy about showcasing relevant projects!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you’re excited about the Lead AWS Data Engineer position and how your background makes you a perfect fit for our team at Deepstreamtech.
Showcase Your Learning Mindset:We love candidates who are eager to learn! Mention any recent courses or projects related to financial analytics or indices. It shows us that you’re not just about the tech, but also about growing in your role.
Apply Through Our Website:Don’t forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it’s super easy – just a few clicks and you’re done!
How to prepare for a job interview at Deepstreamtech
✨Know Your Tech Inside Out
Make sure you brush up on your Python and Apache Spark skills. Be ready to discuss specific projects where you've used these technologies, as well as any challenges you faced and how you overcame them.
✨Understand the AWS Environment
Familiarise yourself with the AWS services relevant to data engineering. Knowing how to leverage tools like S3, Redshift, and Glue will show that you're prepared to work in their modern AWS environment.
✨Show Your Collaborative Spirit
Since you'll be working with various teams, be prepared to discuss how you've successfully collaborated in the past. Share examples of how you communicated effectively and contributed to team success.
✨Express Your Eagerness to Learn
Demonstrate your enthusiasm for financial analytics and indices. Research the company’s focus areas and be ready to discuss how you can contribute to shaping their next-generation data platform.
