Senior Backend/Data Platform Engineer (Audience & Activation Systems)

Apptad Inc.
Frisco, United States of America
12 days ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Languages
English
Experience level
Senior
Compensation
$ 165K

Job location

Frisco, United States of America

Tech stack

Big Data
Program Optimization
Continuous Integration
Customer Data Management
Data Deduplication
Data Infrastructure
Data Security
DevOps
Distributed Systems
Fault Tolerance
Python
Performance Tuning
Redis
Data Streaming
Azure
Data Processing
Spark
Caching
Backend
FastAPI
Build Management
Data Lake
Kubernetes
Low Latency
Kafka
Vertica
Api Design
REST
Stream Processing
User Identification
Databricks
Microservices

Job description

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., * 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

Requirements

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.

Apply for this position