Back
Niche stack (Pinot/Cube) and senior level reduce applicant density.
Specialized OLAP and semantic-layer experience for SaaS analytics limits cross-industry portability.
Multiple mandatory technologies and explicit 7–12 years requirement make filtering stringent.
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Lead architecture and development of real-time customer-facing analytics engine processing millions of events daily.
Design and maintain a low-latency analytics stack supporting thousands of concurrent SaaS users with Apache Pinot and Cube.js.
Build and optimize ingestion pipelines from PostgreSQL and Kafka/Kinesis, develop semantic layer ensuring data consistency and multi-tenant security.
7 to 12 years of relevant work experience.
3+ years production experience with Apache Pinot or similar OLAP technologies.
Deep experience with Cube.js including pre-aggregations and multi-tenant security configurations.
Expert-level PostgreSQL knowledge focused on analytical query optimization and CDC; hands-on experience with real-time ingestion tools (Debezium, Kafka, or Flink).
Experienced in building scalable, low-latency analytics systems with real-time ingestion and semantic modeling expertise.
Skilled in both backend development (Node.js/Python) and complex SQL for translating business logic into data schemas.
Previous exposure to CRM or Sales Tech analytics, and familiarity with infrastructure as code or contributions to relevant open-source projects is advantageous.