Senior Analyst - Data Engineering

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., * 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.

Do you have experience in Spark?, Do you have a Bachelor's degree?, 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., * 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.

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.