Lead/Sr. Backend Engineer

Remote (ON or BC Only)

Our Client is the AI-Powered workforce management software that is radically changing how companies are operated. Reinventing Resource Management, we give visibility into what everyone is working on and help the entire company plan who is doing what, together. Our Client provides the tools needed to connect and manage a modern distributed workforce. This is a rare opportunity to be part of a high-growth venture-backed startup pursuing a world-changing mission.

We are seeking a seasoned Lead/Sr. Software Engineer who is highly proficient in distributed systems and database design. As an early member of our team, you will bring a sophisticated level of problem-solving to elevate our cutting-edge frameworks, patented automation, and AI. This is the best time for inspired individuals to join and contribute their voice, directly impacting the future of the company that’s revolutionizing how companies work.

Responsibilities:

  • Develop complex and highly scaled data processing pipelines in both batch and streaming contexts. Ship new features, improve reliability, correctness, and resolve performance bottlenecks.,

  • Work with cutting-edge technology like Postgres, Redis, ECS, Kubernetes, Dataflow, and BigQuery to power metrics and R&D.

  • Participate in all phases of software development from architecture/design through implementation, testing, and on-call.

  • Work closely with the Data Science team to implement sophisticated statistical methodology into the platform/pipelines.

Requirements:

  • 6+ years in a hands-on engineering role, writing and shipping high-quality production code, especially highly reliable and scalable distributed systems.

  • Experience with at least one of the following languages: Ruby, Python, TypeScript.

  • Experience developing and debugging in a data-heavy environment.

  • Experience with software engineering standard methodologies (e.g. unit testing, code reviews, design documentation).

  • Bonus Points: Experience with one of the following: statistics and causal inference OR stream processing at scale (e.g. Beam/Flink/Storm) OR GCP and related tools.