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 dailyfrom 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:

- Use Cube (Cube.js) to model complex sales metrics (e.g., "Sequence Conversion Rate," "Attributed Revenue," "Meeting Booked Rate") ensuring consistency across the application.

Performance Engineering:

- Optimize Apache Pinot tables, indexing strategies, and Cube pre-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 with Apache Pinot (or similar technologies like ClickHouse/StarRocks) in a production environment.

Semantic Modeling:

- Deep experience with Cube (Cube.js), including advanced features like pre-aggregations, security contexts, and multi-tenant configurations.

Data Store Mastery:

- Expert-level knowledge of PostgreSQL, 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.