At a Glance
- Tasks: Design and build scalable data pipelines while collaborating across teams.
- Company: Join Nasdaq, a leader in financial technology with an inclusive culture.
- Benefits: Competitive salary, bonus, equity options, and hybrid work flexibility.
- Other info: Exciting opportunities for career growth in a dynamic environment.
- Why this job: Make an impact in the financial sector with cutting-edge data engineering.
- Qualifications: Bachelor’s degree in STEM and 2-4 years of data engineering experience.
The predicted salary is between 60000 - 80000 € per year.
Nasdaq, Inc. is seeking a Senior Data Engineer in York and North Yorkshire to design and build scalable data pipelines while collaborating across teams to launch data products.
You'll need a Bachelor’s degree in a STEM field and 2-4 years of experience in data engineering, with skills in Python, SQL, and big data platforms like AWS.
The role offers a competitive salary ranging from $75,000 to $103,000, along with a bonus and equity options, all in a hybrid work environment that promotes inclusivity.
Senior Data Engineer - Financial Data Pipelines (Hybrid) employer: Nasdaq, Inc.
At Nasdaq, Inc., we pride ourselves on being an excellent employer that fosters a collaborative and inclusive work culture in York and North Yorkshire. Our Senior Data Engineers enjoy competitive salaries, bonuses, and equity options, alongside ample opportunities for professional growth and development in a hybrid work environment that values innovation and teamwork.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Data Engineer - Financial Data Pipelines (Hybrid)
✨Tip Number 1
Network like a pro! Reach out to current or former employees at Nasdaq through LinkedIn. A friendly chat can give us insider info and might even lead to a referral.
✨Tip Number 2
Show off your skills! Prepare a portfolio showcasing your data engineering projects, especially those involving Python, SQL, and AWS. This will help us stand out during interviews.
✨Tip Number 3
Practice makes perfect! Get ready for technical interviews by brushing up on your coding skills and data pipeline design. We can use platforms like LeetCode or HackerRank for practice.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets noticed. Plus, we often have exclusive job postings that you won’t find elsewhere.
We think you need these skills to ace Senior Data Engineer - Financial Data Pipelines (Hybrid)
Some tips for your application 🫡
Tailor Your CV:Make sure your CV highlights your experience in data engineering, especially with Python, SQL, and big data platforms like AWS. 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 passionate about data engineering and how you can contribute to our team at Nasdaq. Keep it concise but engaging – we love a good story!
Showcase Collaboration Skills:Since this role involves working across teams, make sure to highlight any collaborative projects you've been part of. We value teamwork, so share examples of how you’ve successfully worked with others to launch data products.
Apply Through Our Website:We encourage you to apply directly through our website for the best chance of getting noticed. It’s super easy, and you’ll be one step closer to joining our inclusive hybrid work environment!
How to prepare for a job interview at Nasdaq, Inc.
✨Know Your Tech Stack
Make sure you brush up on your Python, SQL, and any big data platforms like AWS. Be ready to discuss specific projects where you've used these technologies, as this will show your hands-on experience and technical prowess.
✨Understand the Company Culture
Research Nasdaq's values and work environment. Since they promote inclusivity, think about how your own experiences align with this. Prepare to share examples of how you've contributed to a collaborative team atmosphere in previous roles.
✨Prepare for Scenario-Based Questions
Expect questions that ask you to solve real-world problems related to data pipelines. Practice articulating your thought process clearly, as this will demonstrate your analytical skills and ability to work under pressure.
✨Ask Insightful Questions
At the end of the interview, have a few thoughtful questions ready. Inquire about the team's current projects or challenges they face in launching data products. This shows your genuine interest in the role and helps you gauge if it's the right fit for you.
