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Salary: CAD 186,838 - 334,740 / annual
Braze is seeking a Senior Software Engineer II to join the Decisioning Studio Integrations team, which builds BrazeAI Decisioning Studio™—a reinforcement learning platform that runs continuous experiments to personalize customer engagement. The team owns both the data ingestion pipeline and the delivery channels for RL-driven recommendations.
In this role, you will lead complex integration projects from design through build and rollout, setting technical direction for the Decisioning Studio integration platform. You'll design and build integrations with cloud data warehouses, customer engagement platforms, and other enterprise systems for both data ingestion and activation orchestration. You'll build ingestion pipelines that handle batch pulls, file drops, APIs, and streaming data while accepting arbitrary schemas and preventing bad data from reaching models. You'll also build event-driven, fault-tolerant activation pipelines that deliver recommendations on schedule, recover cleanly from partial failures, and guarantee no duplicate sends.
Additional responsibilities include designing for multi-region deployment and compliance requirements (data residency, PII handling), owning systems in production with Datadog instrumentation and on-call participation, working cross-functionally with data scientists and product managers to turn requirements into reusable platform capabilities, and mentoring engineers while raising the bar for code quality and design review.
This is a high-impact, customer-facing role within a fast-growing company recognized as a leader in marketing technology and customer engagement platforms.
REQUIREMENTS:
- 6+ years of backend engineering experience building and operating distributed systems in production
- Track record of technical leadership: owning complex projects end-to-end, making architecture decisions, setting direction for other engineers
- Experience building data pipelines or integrations moving very large data volumes between systems, including schema changes, backfills, and partial failure handling
- Strong grasp of event-driven architecture and reliability patterns: message brokers (Kafka), idempotency, retries with backoff, dead-letter handling, at-least-once vs. exactly-once tradeoffs
- Proficiency in Python and SQL
- Hands-on experience with cloud infrastructure (GCP preferred) and Kubernetes
- Experience with AI coding assistants and judgment about when they help
- Clear communicator who works well with engineering, data science, and product teams
- Self-starter who finds problems and works around obstacles
BONUS:
- Experience integrating with cloud data warehouses (BigQuery, Snowflake, Redshift)
- Experience integrating with customer engagement platforms (Braze, Adobe, Salesforce Marketing Cloud, Klaviyo)
- Experience building multi-region systems under data residency and compliance requirements
- Experience running ML systems in production
