Lead Engineer

Toronto

Summary

The Lead engineer is a critical part of our Engineering organization. As a member of an experienced engineering team in financial services, you will need to be able to cross boundaries easily and work collegially with highly effective individuals across the data services organization. You will be part of teams working at the forefront of trading applications technology, which include on-premise deployments as well as migration to AWS, big-data ingestion and analytics, distributed systems and algorithmic complexity.

This role is expected to contribute to all parts of the software development and deployment life cycle, including design, development, documentation, testing and operations. You will be working towards a service-oriented architecture and launching data services/micro-services from the ground up, as well as building systems interacting with our trading cores.

The following skill sets provide a good foundation for a quick ramp up to being productive in our environment

Algorithms, design patterns, data structures, Java, Linux and cloud-based development

 

Key Responsibilities

The following duties include, but are not limited to:

  • Work on full-stack analytical applications

  • Responsible for developing highly performant and scalable components that are able to handle large amounts of financial data

  • Help develop distributed systems with concurrent access and usage patterns

  • Work closely with our product team and engineering teams to understand the needs of our clients

 

Qualifications Required

  • Bachelor's Degree in Computer Science, or another quantitative field. Ideally a Master’s degree or above.

  • 7+ years experience delivering highly scalable, fault tolerant, supportable and well architected solutions

  • Strong fundamental knowledge of computer science algorithms, data structures and design patterns

  • Significant cloud platform experience, preferably with AWS

  • Expert level Java or C++

  • Strong Unix and scripting skills

  • Expert knowledge of database systems; relational, NoSQL

  • Experience designing distributed systems at scale handling large data sets leveraging Apache Spark, Kafka, Kinesis, and Hadoop toolsets.

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