Or Sagiv
Data Tech Lead at Riskified
Data Tech Lead at Riskified
Or Sagiv's published DoMLs
The workflow helps teams design and review a scalable Postgres schema for relationship and interaction data such as comments, reactions, and mentions. It transforms inputs like entity types, expected queries, scale, retention, and privacy constraints into a complete technical deliverable. The goal is to provide a normalized, efficient, and privacy‑aware database design with indexes, rationale, query examples, and a migration strategy.
The team needs a structured, low‑disruption workflow for upgrading software dependencies. The workflow must clarify strategy, risks, testing, rollback, and communication while accounting for breaking changes and CI processes. The goal is to ensure predictable releases using practical, calm guidance.
The workflow ensures that new feature launches are prepared, communicated, and executed with minimal risk. It transforms a feature’s scope and rollout plan into a structured readiness checklist, launch communications, monitoring plans, rollback procedures, and a post‑launch review agenda. The goal is to reduce surprises and maintain high operational quality.
created and published a DoML "Release Readiness Checklist (Feature Launch)"
View DoML →created and published a DoML "Postgres Schema Review for Relationship Data"
View DoML →Discussed a conference talk on scaling Airflow for enterprise use based on Riskified’s multi-year journey
View original on LinkedIn →Or shared insights on scaling Apache Airflow into a self-service platform ahead of his hayaData 2025 talk.
View original on LinkedIn →Or Sagiv announced a local Airflow install tool using Helm and Kubernetes to streamline development.
View original on LinkedIn →Or shared insights on hiring for a Big Data Infrastructure Engineer role at Riskified
View original on LinkedIn →Shared content about building Spark Structured Streaming as a service to support teams with scalable Big Data infrastructure
View original on LinkedIn →