AI-Native Sr Data Platform Engineer - Customer Journey Analytics 

Requirements

• 10+ years of hands-on experience building and operating distributed systems, backend services, or large-scale data platforms.

• Strong experience with event streaming and messaging systems (Kafka, Kafka Streams, Flink, Kinesis, or similar).

• Experience building data pipelines using Spark, Databricks, Flink, or comparable technologies.

• Solid understanding of operating production systems: Kubernetes, CI/CD, monitoring, alerting, and incident response.

• Experience crafting and operating scalable REST services.

• Strong engineering fundamentals (Java preferred; Python familiarity a plus).

• A pragmatic approach: you care about correctness, performance, reliability, and cost — not just features.

Nice to Have

• Scala experience.

• Experience with Jenkins, Argo, or similar CI/CD tooling.

• Strong observability background (Prometheus, Grafana, Splunk, Fluentbit).

• Experience operating systems during high-traffic or event-driven spikes.

• Prior exposure to AI-assisted features, LLM APIs, or AI-powered services in production.

• Familiarity with monitoring AI/ML systems (telemetry, drift, performance signals).

What You'll Be Doing

• The role calls for an AI-Native Sr Data Platform Engineer to advance the data and service foundations behind Adobe Analytics and Customer Journey Analytics.

• This is not a pure AI role and not a traditional big-data role. We’re seeking engineers who recognize that AI systems depend heavily on the quality of the platforms supporting them.

Perks and Benefits

• You’ll work on a stable, widely used product, not a greenfield experiment.

• You’ll help define how AI fits into large-scale analytics systems responsibly.

• You’ll operate real systems, with real customers, real traffic, and real consequences.

• You’ll influence platform direction, not just implement tickets.