Data Platform Engineer II

Tasks

• Build and maintain scalable, secure, and reliable data pipelines and platform components across AWS and Snowflake.
• Take ownership of the problems you pick up, holding a high bar for quality, documentation, and engineering craft, and seeing work through to production.
• Help scope and deliver initiatives that modernize legacy data flows, bring together batch and streaming sources, and enable self-serve analytics across the organization.
• Partner with Analytics, ML, Finance, and other business teams to deliver data with the latency, accuracy, and governance their use cases need.
• Help build AI capabilities into data pipelines (e.g., anomaly detection, automated tagging) and use AI in your own development practices (e.g., assisted testing, documentation).

Requirements

• Solid experience building data pipelines using Snowflake and AWS-native tools (e.g., Glue, Lambda, Redshift, Step Functions).
• Fluency in Python and SQL; some exposure to infrastructure-as-code (e.g., Terraform or CDK).
• Working experience with real-time data systems such as Kafka, Kinesis, Flink, or Spark Streaming.
• Good working knowledge of data modeling, schema evolution, and secure, privacy-conscious data design.
• Practical use of AI tools in your development workflow, and interest in building AI into the platform itself.

How to apply

• Explore the opportunity through the provided link.

Location

• Vancouver