Description

You will build scalable audience computation, segmentation, and customer profile serving systems for large-scale datasets. You own the real-time activation pipelines, data platform optimization, and backend API development.

This role is hybrid.

Responsibilities

• Build scalable audience materialization pipelines and identity-aware logic including deduplication and cross-channel resolution.
• Design low-latency customer profile serving systems for real-time lookup and enrichment.
• Develop real-time activation pipelines using Kafka and Azure Event Hubs for event-driven data flows.
• Optimize batch and streaming processing using Databricks, Spark, and Delta Lake for reliability and performance.
• Build and maintain scalable microservices and APIs using Python (FastAPI) deployed on Kubernetes/AKS.

Required Skills

• 5+ years of experience with Python and backend frameworks, specifically FastAPI.
• Strong hands-on experience with Spark and Databricks for large-scale data processing.
• Proficiency with distributed streaming technologies: Kafka or Azure Event Hubs.
• Experience with high-performance analytical stores like ClickHouse or Pinot.
• Solid understanding of distributed systems, microservices architecture, and API design.
• Experience deploying and managing services on Kubernetes (AKS).
• Knowledge of CI/CD practices and monitoring strategies.

Preferred Skills

• Experience with Customer Data Platforms (CDP) or audience segmentation systems.
• Exposure to identity resolution, customer 360, or large-scale dataset (TB/PB) handling.

Key Skills

Education

Bachelor's degree