About This Role 7 to 12 years of experience
Skills: Cube.js, apache pinot
About the Role
We are looking for a Senior Real-time Data Engineer to lead the architecture and development of our customer-facing analytics engine. Our Sales Engagement Platform processes millions of events daily—from email interactions to live call metadata. Your mission is to transform this firehose of raw data into high-performance, actionable insights for our users.
You will bridge the gap between backend data systems and the user interface, building a robust Semantic Layer that ensures our customers see the same "Single Source of Truth" across every dashboard, report, and API.
Key Responsibilities:
- Architecture & Scaling: Design and maintain a low-latency analytics stack capable of handling high-concurrency queries from thousands of concurrent SaaS users.
- **Real-time Ingestion:**Build and optimize ingestion pipelines that move data from transactional databases (PostgreSQL) and event streams (Kafka/Kinesis) into Apache Pinot.
- **Semantic Layer Development:UseCube (Cube.js)**to model complex sales metrics (e.g., "Sequence Conversion Rate," "Attributed Revenue," "Meeting Booked Rate") ensuring consistency across the application.
- Performance Engineering:OptimizeApache Pinottables, indexing strategies, andCubepre-aggregations to ensure dashboard widgets load in under 300ms.
- **API Strategy:**Expose data models via REST/GraphQL APIs, collaborating closely with Frontend Engineers to build world-class data visualizations.
- **Data Governance:**Implement multi-tenant security logic within the semantic layer to ensure strict data isolation between different customer accounts.
Technical Requirements
- OLAP Expertise:3+ years of experience withApache Pinot(or similar technologies like ClickHouse/StarRocks) in a production environment.
- Semantic Modeling:Deep experience withCube (Cube.js), including advanced features like pre-aggregations, security contexts, and multi-tenant configurations.
- Data Store Mastery:Expert-level knowledge ofPostgreSQL, specifically in the context of analytical query optimization and Change Data Capture (CDC).
- **Streaming & Ingestion:**Hands-on experience with real-time data movement (Debezium, Kafka, or Flink).
- **Software Craftsmanship:**Proficiency in Node.js or Python, with a focus on building scalable backend services.
- **Language:**Mastery of complex SQL and the ability to translate business logic into code-based data schemas.
Bonus Points If You Have
- Experience building analytics specifically for CRM or Sales Tech ecosystems.
- Contributions to open-source projects (specifically in the Pinot or Cube communities).
- Experience with Infrastructure as Code (Terraform, Kubernetes) for managing data clusters.