Senior Data Engineer

  • Toronto, ON
  • Posted 15 hours ago | Updated 11 hours ago

Overview

On Site
$130000.0000 - $140000.0000
Full Time

Skills

Python
AWS
SQL
AWS Cloud
Data Engineering
ETL
Airflow
Data engineer
Pipeline
Hybrid
Toronto
Ontario
Fulltime

Job Details

Title: Senior Data Engineer


Duration: Full-time, Permanent


Location: Toronto, ON- Hybrid 3X/Week in office


Start Date: ASAP


Compensation and Benefits: $130K $140K & Benefits: Standard health, dental, vacation, and personal day package (aligned with firm policy)


Interview Process: 3 Rounds


Day-to-Day Responsibilities:



  • Design, build, and maintain scalable, efficient data pipelines integrating data from various market sources (Bloomberg, Morningstar, Nasdaq, etc.).

  • Manage production systems and automate workflows to reduce resolution times.

  • Implement data quality monitoring, governance, and privacy standards in alignment with enterprise policies.

  • Collaborate with data scientists, analysts, and product teams to deliver reliable, well-documented datasets.

  • Support adoption of DevOps culture, building automation and reliability into data operations.

  • Stay up to date on emerging data engineering tools and methodologies.


Must-Haves:



  • Bachelor s degree or college diploma in Computer Science, Engineering, or related field.

  • 4+ years of hands-on data engineering experience.

  • Strong proficiency with AWS data stack: EMR, Glue, Lake Formation, Airflow, PySpark, Trino, Hudi, Iceberg.

  • Proficiency in Python and SQL.

  • Experience with Big Data concepts - change data capture, data quality, data lineage.

  • Knowledge of data governance and quality frameworks.

  • AWS Certified Data & Analytics Specialty (or equivalent).


Nice-to-Haves / Plusses:



  • Experience working with carbon emissions or ESG datasets.

  • Familiarity with enterprise data architecture and governance frameworks.

  • Prior experience in financial services or capital markets (highly preferred).

  • Understanding of market data vendors (Bloomberg, Capital IQ, S&P, Morningstar).

  • Exposure to Scala or additional data engineering languages.


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