Data Engineer - Financial Engineering

What You'll Do

• Work with modern data processing frameworks, platforms, and tooling (Python, Scala, Java, Scio, Flyte, Styx, DBT, etc. on GCP) to build, operate and own reliable data pipelines and systems that support financial forecasting and performance analysis
• Take ownership of existing financial and forecasting datasets, evolving schemas and data models to support new features and analytical use cases while protecting downstream consumers
• Partner closely with engineers, product managers, and finance stakeholders to translate forecasting, planning, and variance analysis needs into well-designed solutions
• Help improve automated financial controls to ensure data quality and compliance across our systems while continuously evaluating performance
• Work in cross-functional, agile teams with end-to-end responsibility for the evolution and operation of long-lived data products

Who You Are

• You have 3+ years of experience in building production-quality data solutions with complex business domain logic
• You have 3+ years of experience using SQL and Python and are comfortable using data to troubleshoot issues and support business decision-making
• You have experience owning data pipelines and datasets end to end, with accountability for maintainability, reliability, and safe evolution over time
• You are a self-motivated contributor who can prioritize and deliver on projects while communicating effectively in a changing environment
• You care deeply about data quality and have implemented monitoring, validation, and reliability best practices in real systems
• You have experience working cross-functionally with engineers, product managers, and non-technical stakeholders
• You value strong engineering practices, including testing, observability, and operational responsibility
• Forecasting or Financial experience is a plus

Where You'll Be

• This role is based in Toronto.
• We offer you the flexibility to work where you work best! There will be some in person meetings, but still allows for flexibility to work from home.