Responsibilities
- Lead the architecture and execution of high-performance, scalable streaming data pipelines.
- Design and refine real-time data processing solutions using technologies such as Apache Kafka, Flink, and Spark Streaming.
- Work closely with product, analytics, and artificial intelligence teams to align data infrastructure with business objectives.
- Support the evolution of systems by expanding the use of event-driven design and cloud-native platforms.
- Promote strong data engineering standards, including governance, monitoring, and performance optimization for streaming workflows.
- Integrate data quality controls into pipelines by defining schema standards, validating transformations, enforcing compatibility in schema changes, and automating validation of data freshness, completeness, and correctness prior to deployment.
- Build comprehensive monitoring capabilities for streaming systems using metrics, logs, and distributed tracing; define service level objectives for latency and throughput; implement alerts and dashboards to support rapid issue resolution.
- Champion engineering excellence by participating in code reviews, offering actionable feedback, and actively soliciting input on personal contributions.
Work Arrangement
Hybrid — Mississauga, Salt Lake City
Travel to office expectations
- For Hybrid Roles, employees must live within commuting distance of the listed office location. Regular in-office attendance is required, including team-specific events on a weekly, bi-weekly, or monthly basis. This is a mandatory requirement for the position.
- For Remote Roles, employees must be able to travel to the Mississauga and/or Salt Lake City office for certain in-person events, including onboarding, team gatherings, and semi-annual or annual meetings.
