Senior Backend Engineer for Petabyte-Scale Activation

LiveRamp; Little Rock, New York (AR, NY); On-site; USD 157,000 - 235,000; Full time

Job summary

LiveRamp is seeking an experienced backend/data engineer to architect and evolve a petabyte-scale activation platform. You will own end-to-end data pipelines, optimize performance and costs, and mentor other engineers in a cloud-native, multi-region environment.

You will work with Spark/Dataproc, SingleStore, Kubernetes, and streaming systems, shaping technical strategy from design through rollout while maintaining reliability and observability.

Qualifications

• 5+ years of experience writing and deploying production code in a modern language (e.g., Java, Go, Scala).
• Experience leading design/delivery of large-scale distributed or big data systems with measurable impact.
• Strong data engineering and SQL skills for complex queries on very large tables.
• End-to-end data pipelines ownership: ingestion, transformation, orchestration, failure handling, observability.

Responsibilities

• Lead the design and evolution of a petabyte-scale activation platform.
• Shape end-to-end technical strategy for Activations Back End.
• Architect and build big data pipelines using Spark/Dataproc, SingleStore, Kubernetes, and streaming systems.
• Use Temporal/Cadence to orchestrate long-running workflows with robust retry and observability.
• Design for multi-tenant fairness and scalable SLAs across many customers.
• Drive performance and cost optimization for large workloads and lead production excellence.

Skills

Production code (Java/Go/Scala)

Cloud experience (GCP)

SQL/data engineering

Mentoring teams

Tools

SingleStore

Spark/Dataproc

Kubernetes/GKE

Pub/Sub/Redpanda

Temporal/Cadence

Job description

LiveRamp is seeking an experienced backend/data engineer to architect and evolve a petabyte-scale activation platform. You will own end-to-end data pipelines, optimize performance and costs, and mentor other engineers in a cloud-native, multi-region environment.

You will work with Spark/Dataproc, SingleStore, Kubernetes, and streaming systems, shaping technical strategy from design through rollout while maintaining reliability and observability.