Senior BackendData Platform Engineer

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.