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. The candidate will work across real-time data ingestion, OLAP systems, semantic

modeling, APIs, performance optimization, and multi-tenant analytics.

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, including: Semantic modeling,



Pre-aggregations,

Security contexts, Multi-tenant configurations

● Expert-level PostgreSQL knowledge, particularly: 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.

● Robust 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.

Ideal Candidate Profile

The ideal candidate should have strong hands-on experience with Apache Pinot + Cube.js in

production environments.

Candidates should be capable of independently handling:

● Real-time data ingestion architecture.

● OLAP data modeling and optimization.

● Semantic-layer design.

● High-concurrency analytics.

● Query and dashboard performance optimization.

● Multi-tenant data security.

● API-based data consumption.

● End-to-end ownership of real-time analytics solutions.

Priority: Candidates with direct Apache Pinot + Cube.js production experience should be

considered first.

Pay: ₹509,523.85 - ₹1,168,850.93 per year

Benefits:

- Provident Fund

Work Location: Remote

📌 Senior Real-Time Data Engineer (India)
🏢 AVISOFT
📍 India