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Data Engineering Specialist
Nasdaq
Toronto, CAN
Full-time
Senior · 6+ years experience
Hybrid
USD 84000-115000 yearly / year
Discovered 3 weeks ago
PythonSQLSparkPySparkDatabricks
Free
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PythonSQLSpark
Key Skills for This Role
PythonSQLSparkPySparkDatabricks
Full Job Posting
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.
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