Senior BackendData Platform Engineer (Audience & Activation Systems)

Job Description:

• Role Overview
  We are looking for a Senior Backend/Data Platform Engineer to design and build scalable audience computation customer profile serving and real-time activation systems.
  This role focuses on large-scale data processing streaming architectures and low-latency data access to enable advanced customer segmentation and activation.

Key Responsibilities

• Audience & Segmentation Systems Build scalable audience computation and segmentation services for large datasets
• Develop audience materialization pipelines (batch/persistent outputs) Implement identity-aware audience logic (deduplication user stitching cross-channel identity resolution)
• Customer Profile & Serving Layer Build and optimize customer profile serving systems for low-latency access
• Enable real-time profile lookup and enrichment for downstream applications Real-Time Activation & Streaming.
• Develop real-time activation pipelines using Kafka / Azure Event Hubs.
• Enable event-driven data flows for audience activation into downstream systems.
• Ensure scalable and reliable stream processing architectures.
• Data Platform & Performance Optimization Optimize audience preview (low-latency queries) and materialization (batch pipelines) Work with: Databricks / Spark for large-scale processing Delta Lake for storage and reliability.
• Click House / Pinot for high-performance analytical queries Use Redis for caching and fast data access.
• Backend & API Development Build scalable APIs and services using Python (FastAPI preferred) Design robust microservices and distributed systems
• Ensure high performance availability and reliability Cloud & DevOps Deploy and manage services on Kubernetes / AKS Implement CI/CD monitoring and scaling strategies
• Ensure fault-tolerant and resilient systems

Required Skills
Strong Python with backend frameworks (FastAPI preferred)
Experience with Spark Databricks Strong knowledge of Delta Lake and ClickHouse/Pinot Hands-on with Kafka / Event Hubs and Redis
Strong understanding of distributed systems and streaming architectures
Experience with Kubernetes / AKS
Nice to Have
Experience with Customer Data Platforms (CDP) / audience systems
Exposure to identity resolution and customer 360 solutions
Experience with large-scale datasets (TB/PB)
Key Expectations
Strong ownership of backend data platform components
Ability to design low-latency high-scale systems
Experience in real-time and batch data processing Strong problem-solving and system optimization skills Business Impact
Enable scalable audience segmentation customer profile serving and real-time activation driving personalization and engagement at scale.