סקירה כללית
Role Summary Builds high-performance, reliable data systems, including real-time pipelines, tracking, and Feature Store foundations — enabling both analytics and ML production. Minimum Requirements (Must Have) ● Strong software engineering fundamentals (clean code, testing, system design) ● Proven experience building real-time, low-latency data services ● Experience operating in production at scale (high throughput, distributed systems) ● Strong background with modern data stack (e.g., Kafka/Kinesis, Spark/Flink/Beam, Snowflake/BigQuery/Redshift) ● Ability to design schemas, ingestion flows, and data quality frameworks ● Experience collaborating with ML teams on feature availability and consistency Preferred Qualifications (Nice to Have) ● Experience supporting ML systems (feature serving, online/offline consistency) ● Production experience with model inference pipelines ● Strong DevOps experience (Docker, Kubernetes, CI/CD) ● Experience with cloud-native architectures (AWS/GCP) ● Experience implementing data observability / lineage frameworks
דרישות המשרה
(Must Have) ● Strong software engineering fundamentals (clean code, testing, system design) ● Proven experience building real-time, low-latency data services ● Experience operating in production at scale (high throughput, distributed systems) ● Strong background with modern data stack (e.g., Kafka/Kinesis, Spark/Flink/Beam, Snowflake/BigQuery/Redshift) ● Ability to design schemas, ingestion flows,
