Software Engineer, Data Platform
About Us: Notion helps you build beautiful tools for your life’s work. In today's world of endless apps and tabs, Notion provides one place for teams to get everything done, seamlessly connecting docs, notes, projects, calendar, and email—with AI built in to find answers and automate work.
What this role actually needs.
About Us: Notion helps you build beautiful tools for your life’s work. In today's world of endless apps and tabs, Notion provides one place for teams to get everything done, seamlessly connecting docs, notes, projects, calendar, and email—with AI built in to find answers and automate work. Responsibilities: - Design and evolve the data lakehouse Build and operate core lakehouse components (e.g., Iceberg/Hudi/Delta tables, catalogs, schema management) that serve as the source of truth for analytics, AI, and search. - Own critical data pipelines and services Design, implement, and harden batch and streaming pipelines (Spark, Kafka, etc.) that move and transform data reliably across regions. - Advance EKM and encryption-by-design Work with Security and platform teams to integrate Enterprise Key Management (EKM) into data workflows, including file- and record-level encryption and safe key handling in Spark and storage systems. - Improve data access, auditability, and residency Build primitives for fine-grained access control, auditing, and data residency so customers can see who accessed what, where, and under which guarantees. - Drive reliability and observability Raise the operational bar for our data stack: improve on-call experience, debugging, and alerting for data jobs and services. - Optimize large-scale performance and cost Tackle performance and cost challenges across Kafka, Spark, and storage for very large workspaces (20k+ users, multi-cell deployments) Company context: Notion is a product-led software company building connected docs, wikis, AI workflows, and productivity systems.
Day-to-day expectations
Notion lists these responsibilities for the Software Engineer, Data Platform role.
- Design and evolve the data lakehouse Build and operate core lakehouse components (e.g., Iceberg/Hudi/Delta tables, catalogs, schema management) that serve as the source of truth for analytics, AI, and search.
- Own critical data pipelines and services Design, implement, and harden batch and streaming pipelines (Spark, Kafka, etc.) that move and transform data reliably across regions.
- Advance EKM and encryption-by-design Work with Security and platform teams to integrate Enterprise Key Management (EKM) into data workflows, including file- and record-level encryption and safe key handling in Spark and storage systems.
- Improve data access, auditability, and residency Build primitives for fine-grained access control, auditing, and data residency so customers can see who accessed what, where, and under which guarantees.
- Drive reliability and observability Raise the operational bar for our data stack: improve on-call experience, debugging, and alerting for data jobs and services.
- Optimize large-scale performance and cost Tackle performance and cost challenges across Kafka, Spark, and storage for very large workspaces (20k+ users, multi-cell deployments)
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Source: jobs.ashbyhq.com · Source ID: 91156750-4050-4621-aa45-0fb068308d2c · Confidence: 93/100 · Last checked: May 7, 2026
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