Job Title:Senior Backend/Data Platform Engineer (Audience & Activation Systems)
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 ClickHouse / 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.