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Lead Data Engineer

Nasdaq

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7,267 open data roles across 646 companies are on ApplySarthi right now, most of them in Bengaluru (415), Hyderabad (313), Mumbai (155).

What data roles keep asking for: AWS (24%), SQL (22%), Python (22%) — counted across their open postings here.

Data Engineer jobs in Canada · Remote Data Engineer jobs · Databricks jobs · Python jobs · SQL jobs · Spark jobs

Nasdaq has 176 open roles listed here.

Counted across 14 company job boards, updated as roles open and close.

Preparing for this interview

Interviews for data roles keep coming back to AWS, SQL, Python. Practise those questions before you sit with Nasdaq.

Questions you are likely to be asked

  1. Why do you want to join Nasdaq?
  2. What is your experience with Spark? Tell me one thing you learned the hard way.
  3. What would you check first if a model's accuracy dropped after going live?
  4. When would you not use machine learning for a problem?
  5. Walk me through a model you built, from the data to how it was used.

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As a Lead Data Engineer reporting to the Senior Director of Data Engineering, you'll play a critical role in designing, building, and scaling the data infrastructure that powers one of the world's largest data marketplaces — serving hundreds of thousands of professionals across finance, technology, and beyond. You'll thrive in this position if you're analytical, detail-oriented, and passionate about data quality and engineering excellence in a fast-paced, high-impact environment. Key Responsibilities Design, implement, and maintain components of our data platform, with a strong focus on data onboarding and automation. Build and optimize data ingestion pipelines that clean, transform, and load large volumes of structured and unstructured data. Develop automated data processing, transformation, and quality assurance workflows to ensure completeness, accuracy, and reliability. Write and manage distributed data pipelines supporting both real-time and batch processing across cloud environments. Champion a collaborative code review culture that promotes maintainability, best practices, and continuous improvement. Required Qualifications Bachelor's degree in Computer Science, Engineering, or equivalent practical experience. 10+ years of professional experience in software or data engineering. Proficiency in Python (required), with working knowledge of SQL and Spark/PySpark. Hands-on experience with cloud platforms and data tools, including distributed data pipeline development and orchestration. Strong written and verbal communication skills in English, with the ability to document clearly and concisely. Preferred Qualifications Experience building and integrating AI tools into data engineering workflows. Data engineering certification (e.g., Databricks Certified Data Engineering Associate or Professional). Prior experience in fintech, capital markets, or a regulated data environment. This position will be located in Toronto, Canada, 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 $106,000 - $148,000. 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.

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Listed on workday · posted 2026-08-27. ApplySarthi collects openings and links to application pages; the role is advertised by Nasdaq, not by us.