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Staff Software Engineer (MIP tech lead)
Proofpoint
Toronto, CAN
Onsite
Discovered 2 weeks ago
Enterprise-scale data engineeringIdempotency, deduplication, and data quality validationObservability and SLOsKafkaStreaming and event-driven systemsJava
Free
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Ready to ScanKey skills for this role
Enterprise-scale data engineeringIdempotency, deduplication, and data quality validationObservability and SLOs
Role Overview
The Toronto-based Archiving Ingestion team is seeking a Staff Software Engineer to serve as technical lead for ingestion and data engineering across DCG.
The ingestion platform processes millions of messages daily across email, collaboration, and cloud connectors.
The role will shape how data enters the platform, including cost, reliability, and operational guarantees.
Key Skills for This Role
Enterprise-scale data engineeringIdempotency, deduplication, and data quality validationObservability and SLOsKafkaStreaming and event-driven systemsJava
Full Job Posting
About Proofpoint
Proofpoint develops cybersecurity products that protect people, data, and AI agents across email, cloud, and collaboration tools.
The Digital Communications Governance Archive supports mission-critical data ingestion, storage, and retrieval for large enterprises.
The Role
The Toronto-based Archiving Ingestion team is seeking a Staff Software Engineer to serve as technical lead for ingestion and data engineering across DCG.
The ingestion platform processes millions of messages daily across email, collaboration, and cloud connectors.
The role will shape how data enters the platform, including cost, reliability, and operational guarantees.
What You Will Own
- Own architectural direction for the ingestion platform, including Kafka topology, EKS deployment models, feature design, and API design.
- Drive a scalable and robust ingestion platform roadmap.
- Set engineering standards for code quality, observability, and incident response.
- Define and own ingestion SLOs for throughput, latency, data quality, and related measures.
- Lead root-cause analyses, failure mitigation, and systemic incident reduction.
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