At a Glance
- Tasks: Design and build scalable data pipelines for innovative financial products.
- Company: Join Nasdaq, a leader in financial technology with a collaborative culture.
- Benefits: Competitive salary, bonuses, equity, and comprehensive benefits package.
- Other info: Hybrid work environment with opportunities for growth and inclusivity.
- Why this job: Make an impact in the fast-paced world of data engineering and finance.
- Qualifications: Bachelor's degree in STEM and 2-4 years of data engineering experience required.
The predicted salary is between 75000 - 103000 € per year.
As a Senior Data Engineer reporting to the Director of Data Science, you'll play a critical role in building and scaling innovative data products that power some of the world's most successful financial organizations — from traditional market data to cutting-edge alternative data sources. You'll thrive in this position if you're curious, data-driven, and collaborative, with a passion for financial technology and a drive to deliver reliable, high-quality solutions in a fast-moving environment.
Key Responsibilities
- Design, build, and maintain scalable data pipelines — covering ingestion, transformation, enrichment, and delivery of financial and alternative datasets.
- Partner with Data Science, Product Management, and Engineering teams to develop and launch new data products.
- Ensure the quality, accuracy, timeliness, and completeness of data products through robust monitoring and quality frameworks.
- Contribute to the onboarding of new data sources, including exchange data and non-traditional alternative data (e.g., satellite imagery, consumer transactions).
- Support continuous improvement of existing data products and infrastructure to enhance performance and reliability.
Required Qualifications
- Bachelor's degree in Computer Science, Engineering, or a related STEM field, or equivalent practical experience.
- 2–4 years of experience in data engineering, with hands-on proficiency in Python, SQL, PySpark/Spark, Java, and shell scripting.
- Experience working with cloud and big data platforms such as AWS (S3/EC2) and Databricks in a Linux environment.
- Solid understanding of version control practices using Git or equivalent tools.
- Strong communicator with the ability to collaborate effectively across technical and non-technical teams.
Preferred Qualifications
- Proven knowledge of financial markets data, including equities pricing, volumes, and fundamentals.
- Experience building or maintaining financial data products in a production environment.
- Familiarity Kafka in a data engineering context.
This position will be located in Toronto and offers the opportunity for a hybrid work environment at least 3 days a week in-office, subject to change, providing flexibility and accessibility for qualified candidates.
Come as You Are
Nasdaq is an equal opportunity employer. We welcome applications from candidates of all backgrounds and identities. We are committed to fostering an inclusive workplace where diverse perspectives, experiences, and identities are valued and celebrated. We ensure that individuals with disabilities are provided with reasonable accommodation throughout the hiring process.
What We Offer
We’re proud to offer a competitive rewards package that is meaningful, recognizes the unique needs of our employees and their families and incentivizes employees for their contribution to Nasdaq’s overall success. The base pay range for this role is $75,000 - $103,000. In addition to base salary, Nasdaq provides a generous annual bonus/commission (short-term incentive), and equity (long-term incentive), comprehensive benefits, and opportunity for growth. Exact compensation may vary based on several job-related factors that are unique to each candidate, including but not limited to: skill set, experience, education/training, business needs and market demands.
Senior Analyst - Data Engineering employer: Nasdaq, Inc.
At Nasdaq, we pride ourselves on being an exceptional employer, offering a dynamic work culture that fosters collaboration and innovation in the heart of Toronto. Our commitment to employee growth is reflected in our competitive rewards package, comprehensive benefits, and a hybrid work environment that promotes flexibility. Join us to be part of a diverse team where your contributions are valued, and you can thrive in the fast-paced world of financial technology.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Analyst - Data Engineering
✨Network Like a Pro
Get out there and connect with folks in the industry! Attend meetups, webinars, or even just grab a coffee with someone who works in data engineering. Building relationships can open doors that a CV just can't.
✨Show Off Your Skills
Don’t just talk about your experience; demonstrate it! Create a portfolio showcasing your projects, especially those involving Python, SQL, or cloud platforms. This gives potential employers a taste of what you can do.
✨Ace the Interview
Prepare for technical interviews by brushing up on your coding skills and understanding data engineering concepts. Practice common interview questions and be ready to discuss your past projects in detail.
✨Apply Through Our Website
When you find a role that excites you, apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are proactive!
We think you need these skills to ace Senior Analyst - Data Engineering
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the Senior Analyst - Data Engineering role. Highlight your experience with data pipelines, cloud platforms, and any relevant financial technology projects. We want to see how your skills align with what we're looking for!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to express your passion for data engineering and financial technology. Share specific examples of your work that demonstrate your curiosity and collaborative spirit. Let us know why you’re excited about this opportunity!
Showcase Your Technical Skills:Don’t forget to highlight your technical skills in Python, SQL, and any experience with big data platforms like AWS or Databricks. We love seeing hands-on experience, so be sure to mention any projects where you've used these tools effectively.
Apply Through Our Website:We encourage you to apply through our website for the best chance of getting noticed. It’s super easy, and you’ll be able to keep track of your application status. Plus, we love seeing candidates who take the initiative to connect with us directly!
How to prepare for a job interview at Nasdaq, Inc.
✨Know Your Data Engineering Tools
Make sure you brush up on your skills with Python, SQL, and PySpark. Be ready to discuss how you've used these tools in past projects, especially in building scalable data pipelines. This will show that you're not just familiar with the tech but can also apply it effectively.
✨Understand Financial Data
Since this role involves working with financial datasets, take some time to familiarise yourself with key concepts like equities pricing and market fundamentals. Being able to speak knowledgeably about these topics will demonstrate your genuine interest in the field and make you stand out.
✨Collaboration is Key
Prepare examples of how you've successfully collaborated with cross-functional teams in the past. Highlight your communication skills and how you've worked with both technical and non-technical stakeholders. This will show that you can thrive in a collaborative environment, which is crucial for this role.
✨Ask Insightful Questions
At the end of the interview, don’t forget to ask questions! Inquire about the team’s current projects or challenges they face with data products. This shows your curiosity and eagerness to contribute, plus it gives you valuable insights into the company culture and expectations.
