Sr. Data Engineer - Toronto, ON (Hybrid)

Location: Toronto, ON (4 Days onsite/week) Start date: ASAP Project Description We are seeking a hands-on Data Engineer to support the Total Fund Management Portfolio Management Technology team. This role focuses on building and optimizing large-scale data processing systems in a cloud-native environment. You are expected to independently design and deliver scalable data solutions with minimal oversight. This is not a role for someone who requires detailed task breakdowns or constant direction. Once objectives and constraints are clear, you are expected to independently drive work to completion, proactively manage risks, and communicate progress effectively. This role is for subcontractors engagement. 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 - Must have Strong Python with PySpark Hands-on experience with Apache Spark (preferably in 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 Nice to have AWS data services (Glue, Lake Formation) Workflow orchestration tools (Airflow) Experience with distributed data processing architectures Capital markets experience Why This Role Opportunity to directly impact business growth by identifying and hiring the right IT talent for critical projects. Hands-on exposure to diverse technologies and stakeholders, strengthening recruitment and domain expertise. Company Name: Pozent Pozent is a rapidly growing company focused on delivering next-generation digital, data, and AI-driven solutions to global clients and achieve measurable business outcomes. Our team is geared towards innovation and thrives where talent meets opportunity. We work on Generative AI, Cloud, Data Engineering, Automation, and Full-Stack Development, delivering impactful projects Why Join Us Exciting Global Projects and career growth: Work directly with top clients and cutting-edge technologies providing a rapid learning curve, skill development, and clear career progression. Innovation Culture and supportive environment: You are not just joining a company — you're becoming part of a dynamic innovation ecosystem that empowers you to learn, explore, create, grow and lead.

The role involves designing and optimizing large-scale Spark-based data processing systems in a cloud-native environment. The engineer will collaborate with stakeholders to translate requirements into robust, maintainable engineering solutions.

Candidates must have strong expertise in Python, PySpark, and Databricks, with experience in columnar formats like Parquet and Iceberg. Proven ability to deliver independently in ambiguous environments and prior consulting experience are required.

• PythonPreferred

Identified from the job description. Confirm important requirements above.

• Python
• PySpark
• Apache Spark
• Databricks
• Parquet
• Iceberg
• AWS Glue
• AWS Lake Formation
• Airflow
• Distributed Data Processing
• Capital Markets
• Cloud-native Data Engineering

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

Minimum experience

5+ years

Apply by

Aug 25, 2026

Posting language

English

Working hours

40 hours per week

Office presence

4 days per week

Seniority

Mid-Senior level