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Data Engineering Specialist

  • Toronto, ON, Canada

The base pay range for this role is $84,000 - $115,000. · Full-time

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Job details

Pay
The base pay range for this role is $84,000 - $115,000.
Job type
Full-time
Experience
5-7 years of professional experience in software or data engineering.
Posting language
English
Posted

Original job description

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.
More about this job

Responsibilities

Design, build, and scale data infrastructure while managing data onboarding and automation processes. Develop and optimize distributed data pipelines to ensure the accuracy, reliability, and quality of large-scale data sets.

Requirements

Requires a bachelor's degree in Computer Science or Engineering and 5-7 years of professional experience in software or data engineering. Proficiency in Python, SQL, and Spark is mandatory, along with hands-on experience in cloud-based data pipeline development.

Skills

  • Python
  • SQL
  • Spark
  • PySpark
  • Data engineering
  • Data pipelines
  • Cloud platforms
  • Data ingestion
  • Automation
  • Data quality
  • Distributed systems
  • Code review
  • Data infrastructure
  • ETL
  • Data transformation

Benefits

  • Annual bonus
  • Equity
  • Comprehensive benefits

Visa sponsorship

Not detected in the job text

Categories

  • Data & Analytics
  • Software
  • Engineering
  • Technology
  • Finance & Accounting

Keywords

  • Data Engineering
  • Python
  • SQL
  • Spark
  • PySpark
  • Cloud Platforms
  • Data Pipelines
  • Automation
  • Data Quality
  • Distributed Systems
  • ETL
  • Fintech
  • Capital Markets
  • Data Infrastructure
  • Databricks
  • AI Tools
  • Software Engineering
  • Data Marketplace
  • Batch Processing
  • Real-time Processing

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