Jobs · Engineering

Senior Integration Engineer

InvestM Technology LLC · United States · 5 days ago
RemoteRemoteEngineeringContract

Responsibilities

  • Design and build CDP activation pipelines — including audience feeds, event streaming, and data quality checks between customer data sources and downstream marketing platforms
  • Own API integration architecture across vendor systems — define contracts, enforce SLAs, and build reliability patterns (circuit breakers, retry logic, dead letter queues)
  • Implement and maintain event streaming infrastructure using Kafka, Azure Service Bus, or comparable message queue / pub-sub systems
  • Build and maintain real-time data pipelines supporting audience delivery and experiment results into marketing data lakes
  • Maintain end-to-end integration health across the martech vendor ecosystem — proactive telemetry, alerting, and incident response
  • Partner with engineering and product teams to onboard new vendor integrations and manage the technical complexity of platform consolidation
  • Document integration patterns, data contracts, and API standards for internal developer use

Required Skills & Experience

  • Integration or backend engineering experience, preferably in martech or data platform contexts
  • Strong API engineering skills — RESTful design, event-driven architecture, webhook/message queue patterns
  • Hands-on experience with Kafka, Azure Service Bus, or similar event streaming/pub-sub platforms
  • Familiarity with vendor integration patterns in martech ecosystems (ESPs, CDPs, tag management, attribution platforms)
  • Cloud-native development experience — Azure preferred; containerization, infrastructure-as-code (Terraform)
  • Strong understanding of data contracts, SLA monitoring, and observability practices

Nice to Have

  • Experience building CDP activation pipelines — Amperity, Segment, or comparable; audience feeds and real-time event streaming
  • Experience with CDP-to-ESP data feed pipelines (e.g., Amperity to downstream activation platforms)
  • Familiarity with GCP data lake architectures (BigQuery, Pub/Sub)
  • Retail or e-commerce domain background
  • Exposure to feature flag systems or experimentation tracking pipelines

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