Senior Cloud Data Engineer – Spark & Python (Toronto)

Pozent Corporation; Toronto; On-site; CAD 90,000 - 135,000; Full time

Job summary

Pozent is seeking a hands-on Data Engineer to support the Total Fund Management Portfolio Management Technology team. You will design and deliver scalable data solutions in a cloud-native environment, focusing on Spark workloads and large-scale datasets.

This is a subcontractor engagement requiring proactive, independent work with strong communication to stakeholders. The role emphasizes delivery without detailed guidance, production readiness, and collaboration across teams to meet objectives.

Qualifications

• Strong Python with PySpark
• Hands-on experience with Apache Spark (cloud environments)
• Experience working with large-scale data systems
• Familiarity with columnar formats (Parquet) and modern table formats (Iceberg)
• Experience with Databricks
• Prior consulting, advisory, or client-facing delivery experience
• Ability to operate effectively in ambiguous environments
• Proven independent delivery without close supervision
• Strong problem-solving and continuous improvement mindset

Responsibilities

• Develop and optimize Spark-based workloads in cloud environments
• Work with large-scale datasets using modern storage formats
• Collaborate with stakeholders to translate data requirements into robust engineering solutions
• Ensure high performance, reliability, and maintainability of data platforms
• Contribute to production readiness, including monitoring, documentation, and deployment

Skills

Python PySpark

Apache Spark

Big data systems

Parquet

Iceberg

Databricks

Client-facing

Ambiguity tolerance

Independent delivery

Problem solving

Continuous improvement

AWS Glue

Airflow

Distributed architectures

Capital markets

Tools

Databricks

Job description

Pozent is seeking a hands-on Data Engineer to support the Total Fund Management Portfolio Management Technology team. You will design and deliver scalable data solutions in a cloud-native environment, focusing on Spark workloads and large-scale datasets.

This is a subcontractor engagement requiring proactive, independent work with strong communication to stakeholders. The role emphasizes delivery without detailed guidance, production readiness, and collaboration across teams to meet objectives.