Data Engineering Specialist

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. 6+ 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 $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.

Design, implement, and maintain the data platform with a focus on automated data onboarding and ingestion pipelines. Develop distributed data pipelines for real-time and batch processing while ensuring data quality and reliability.

Requires a Bachelor's degree in Computer Science or Engineering and over 6 years of professional software or data engineering experience. Proficiency in Python, SQL, and Spark/PySpark is essential, along with hands-on cloud platform experience.

• Annual Bonus • Commission • Equity • Comprehensive Benefits

Relevées dans la description du poste. Confirmez les exigences importantes ci-dessus.

• Python
• SQL
• Spark
• PySpark
• Cloud Platforms
• Data Pipeline Development
• Data Orchestration
• Data Ingestion
• Data Transformation
• Distributed Data Pipelines
• Real-time Processing
• Batch Processing
• Data Quality Assurance
• AI Integration
• Code Review
• Workplace Inclusivity
• Pipelines
• Financial Technology (FinTech)
• Workflow Management
• Automation
• Capital Markets
• Computer Science
• Data Processing
• Continuous Improvement Process
• Data Engineering
• Data Infrastructure
• Data Quality
• Distributed Data Store
• English Language
• Finance
• Equities
• Python (Programming Language)
• Maintainability
• Quality Assurance
• SQL (Programming Language)
• Unstructured Data
• Verbal Communication Skills
• Reliability
• Databricks
• Detail Oriented

• Data & Analytics
• Technology
• Engineering
• Software
• Finance & Accounting
• Data Engineering Manager
• Data Engineer
• Software Developers
• Database Administrators

Formation minimale

Diplôme professionnel

Expérience minimale

5+ ans

Langue de l’offre

anglais

Heures de travail

40 heures par semaine

Présence au bureau

3 jours par semaine