Streaming Data Engineer - Kafka, Flink, Apache Pinot

Bounteous; Hyderabad, Gurugram District, Bengaluru; Hybrid; INR 1,200,000 - 1,800,000; Full time

Job summary

Bounteous is seeking an experienced Data Engineer to design and scale a real-time analytics platform. You will work with Apache Pinot, Cube.js, and modern data tools to build low-latency pipelines and semantic data models.

The role involves building APIs for dashboards, optimizing queries, and ensuring data governance across multi-tenant environments. Strong SQL, Python/Node.js, and streaming experience are required.

Qualifications

• Strong hands-on experience with real-time data pipelines and low-latency analytics.
• Proficiency in SQL and data modeling for analytics platforms.
• Experience with modern BI/analytics stacks and APIs for dashboards.

Responsibilities

• Design and optimize real-time analytics solutions using Apache Pinot.
• Build and maintain semantic data models using Cube.js.
• Develop scalable ingestion pipelines from PostgreSQL and streaming platforms.
• Optimize query performance, indexing, and aggregations for low-latency analytics.
• Build APIs and data services for customer-facing dashboards and reporting platforms.
• Ensure data governance, security, and multi-tenant access controls.

Skills

Advanced SQL

Python

Node.js

Real-Time Data Pipelines

Analytics / OLAP Systems

Tools

Apache Pinot

Cube.js

PostgreSQL

Kafka

Flink

Debezium

Kubernetes

Terraform

GraphQL

ClickHouse

StarRocks

Job description

Role Overview

We are looking for an experienced Data Engineer with strong expertise in Apache Pinot and Cube.js to build and scale our real-time analytics platform. The ideal candidate should have hands-on experience in designing low-latency analytics systems, real-time data pipelines, semantic data modeling, and customer-facing analytics solutions.

Mandatory Skills

• Apache Pinot
• Cube.js (Semantic Layer)
• PostgreSQL
• Kafka / Flink / Debezium
• Advanced SQL
• Python or Node.js
• Real-Time Data Pipelines
• Analytics / OLAP Systems

Key Responsibilities

• Design and optimize real-time analytics solutions using Apache Pinot.
• Build and maintain semantic data models using Cube.js.
• Develop scalable ingestion pipelines from PostgreSQL and streaming platforms.
• Optimize query performance, indexing, and aggregations for low-latency analytics.
• Build APIs and data services for customer-facing dashboards and reporting platforms.
• Ensure data governance, security, and multi-tenant access controls.

Good to Have

• ClickHouse or StarRocks
• GraphQL
• Kubernetes
• Terraform
• CRM or Sales Analytics domain experience