Data Engineering Specialist
At a glance
Mid-level Data Engineering role at Nasdaq. CA-Toronto-York St 24/25 · full-time · CA$84,000–CA$115,000 base.
dataroles summary, based on the employer's posting.
What you'll do
- Build and maintain data platform components, focusing on onboarding datasets and automating the work
- Create pipelines that ingest large structured and unstructured datasets, then clean and reshape them for loading
- Automate data processing and checks so datasets are complete, accurate and dependable
- Run distributed pipelines for both real-time and batch workloads across cloud environments
- Review code with colleagues to improve maintainability, engineering practices and ongoing quality
What you bring
- A computer science or engineering degree, or equivalent practical experience
- Five to seven years working professionally in software or data engineering
- Strong Python skills, plus working knowledge of SQL and Spark or PySpark
- Practical experience with cloud platforms, data tools, distributed pipelines and orchestration
- Clear written and spoken English, including concise technical documentation
Who this fits
This role suits a mid-career data engineer who values data quality and careful, collaborative engineering. You’ll report to the Senior Director of Data Engineering. Preferred extras include integrating AI tools into engineering workflows, a data engineering certification, or experience in fintech, capital markets or regulated data.
From the employer
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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