Job Summary :

We are looking for a Senior Real-Time Data Engineer to lead the architecture and development of a high-performance, customer-facing analytics engine. The role focuses on processing millions of real-time events and transforming raw data into reliable, actionable insights.

Key Responsibilities :

- Design and maintain a low-latency analytics architecture capable of supporting high-concurrency queries.

- Build and optimize real-time ingestion pipelines from PostgreSQL and event streams such as Kafka/Kinesis into Apache Pinot.

- Develop semantic models using Cube.js to create consistent business metrics across dashboards, reports, and APIs.

- Optimize Apache Pinot tables, indexing strategies, and Cube.js pre-aggregations for high-performance analytics.

- Design and expose data models through REST/GraphQL APIs.

- Collaborate with frontend engineers to support analytics and data visualization requirements.

- Implement multi-tenant security and ensure strict data isolation between customer accounts.

- Optimize analytical queries, data pipelines, and backend services for scalability and low latency.

- Translate complex business requirements into scalable data models and semantic-layer implementations.

Must-Have Skills :

- 7 - 12 years of experience in Data Engineering / Analytics Engineering.

- 3+ years of production experience with Apache Pinot or similar OLAP technologies such as ClickHouse/StarRocks.

- Strong hands-on experience with Cube.js (Semantic modeling, Pre-aggregations, Security contexts, Multi-tenant configurations).

- Expert-level PostgreSQL knowledge (Analytical query optimization, Complex SQL, Performance tuning, CDC).

- Hands-on experience with real-time data ingestion and streaming technologies : Kafka, Kinesis, Debezium, Flink.

- Strong proficiency in SQL and ability to translate business logic into data models.

- Strong programming experience in Python or Node.js.

- Experience developing scalable backend services and APIs.

Preferred Skills :

- Experience building analytics platforms for CRM, Sales Technology, or SaaS products.

- Experience with Terraform and Kubernetes.

- Experience managing and scaling data clusters.

- Open-source contributions to Apache Pinot, Cube.js, or related projects.

- Experience with REST and GraphQL APIs.

- Strong understanding of distributed systems and real-time analytics architecture.