3 hours ago
Base Salary
$156k - $280k/yr
Responsibilities
- Lead complex integration projects from design through build and rollout while setting technical direction for the integration platform.
- Design and build integrations with cloud data warehouses, customer engagement platforms, and enterprise systems for data ingestion and activation orchestration.
- Build large-scale ingestion pipelines supporting batch pulls, file drops, APIs, streaming, arbitrary schemas, schema changes, and backfills.
- Build event-driven, fault-tolerant activation pipelines with retries, failure recovery, idempotency, and reliable recommendation delivery.
- Design multi-region systems that address data residency, compliance, and PII handling requirements.
- Own systems in production through Datadog instrumentation, on-call participation, and root-cause incident resolution.
- Collaborate with data scientists, ML engineers, and product managers to turn integration requirements into reusable platform capabilities.
- Mentor engineers and improve code quality, testing, and design review practices.
Requirements
- 6+ years of backend engineering experience building and operating distributed systems in production.
- Demonstrated technical leadership through end-to-end project ownership, architecture decisions, and setting direction for other engineers.
- Experience building high-volume data pipelines or integrations, including schema changes, backfills, and partial failures.
- Strong understanding of event-driven architecture and reliability patterns, including message brokers, idempotency, backoff retries, dead-letter handling, and at-least-once versus exactly-once tradeoffs.
- Proficiency in Python and SQL.
- Hands-on experience with cloud infrastructure, with GCP preferred, and Kubernetes.
- Experience with AI coding assistants and sound judgment about their use.
- Clear communication and effective collaboration with engineering, data science, and product teams.
- Experience with cloud data warehouses such as BigQuery, Snowflake, or Redshift is preferred.
- Experience with customer engagement platforms such as Braze, Adobe, Salesforce Marketing Cloud, or Klaviyo is preferred.
- Experience building multi-region systems under data residency and compliance requirements is preferred.
- Experience running ML systems in production is preferred.
Benefits
- Base compensation for U.S. candidates is listed separately, with potential equity through restricted stock units.
- Retirement and Employee Stock Purchase Plans.
- Flexible paid time off and comprehensive medical, dental, vision, life, and disability coverage.
- Fertility benefits and equal paid parental leave.
- Professional development through career pathing, learning platforms, and a yearly learning stipend.
- Hybrid ways of working and a curated in-office employee experience.
- Volunteer Week, donation matching, and Employee Resource Groups.
- The posting is marked hybrid (#LI-Hybrid).
Tech Stack
Categories
BackendData Engineering
About Braze
Braze builds a customer engagement platform used by marketing teams to orchestrate cross-channel messaging across mobile, email, web, and more. The company sells its software via SaaS subscriptions with analytics, segmentation, and journey orchestration. Founded in 2011 and headquartered in New York, Braze is a public company (NASDAQ: BRZE) with global offices.