Data Engineering Specialist
Nasdaq
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7,130 open engineering roles across 734 companies are on ApplySarthi right now, most of them in Bengaluru (364), Hyderabad (129), Mumbai (54).
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What engineering roles keep asking for: Python (22%), AWS (21%), Observability (14%), System design (13%), CI/CD (12%) — counted across their open postings here.
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Counted across 14 company job boards, updated as roles open and close.
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Questions you are likely to be asked
- Why do you want to join Nasdaq?
- What is your experience with Spark? Tell me one thing you learned the hard way.
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- Walk me through a model you built, from the data to how it was used.
- How did you know your model was actually good, and not just good on your test set?
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Practise the Data Engineering Specialist at Nasdaq interview free →Job Description As a Data Engineering Specialist 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. 5-7 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. 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 $84,000 - $115,000. 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 2026-11-10. ApplySarthi collects openings and links to application pages; the role is advertised by Nasdaq, not by us.