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Salary: USD 156,500 - 235,000 / annual
LiveRamp is a data collaboration platform serving hundreds of global innovators—from consumer brands and tech giants to banks, retailers, and healthcare leaders. The Activations Backend team is responsible for the bulk of big data processing powering LiveRamp's primary activation product, which delivers hundreds of millions in annual recurring revenue. The team processes over 100,000 batch jobs per day, ranging from gigabytes to over 100 terabytes, and powers distributions to hundreds of downstream destinations, cumulatively processing multiple exabytes per year.
In this Staff Backend Software Engineer role, you will lead the design and evolution of a petabyte-scale activation platform. You will shape end-to-end technical strategy for major areas of Activations Backend (e.g., matching/delta computation, job orchestration, delivery pipelines), from design through rollout and long-term maintenance. Key responsibilities include:
- Re-architect Activations Backend to be cloud-forward and multi-regional, leveraging SingleStore and modern data warehouses to replace legacy Spark-heavy flows where appropriate.
- Deliver high-throughput, low-latency activation by combining SingleStore-backed state and delta computation, Spark/Dataproc for heavy batch workloads, and streaming infrastructure (Redpanda/Pub/Sub) for event-driven and incremental deliveries.
- Build smarter orchestration and scheduling using Temporal/Cadence and queueing services to classify jobs, route them through multi-queue schedulers, respect destination-specific rate limits and SLAs, and eliminate duplicated work through config canonicalization and caching.
- Architect and build big data pipelines using Apache Spark/Dataproc, SingleStore, Kubernetes/GKE, and streaming systems.
- Design for multi-tenant fairness and scalability, ensuring small latency-sensitive jobs stay fast while large backfills do not starve the system.
- Drive performance and cost optimization for petabyte-scale workloads: reduce duplicate processing, improve cache hit rates, tune cluster sizing and autoscaling policies, and set and track SLOs.
- Lead production excellence: own critical services in production, coordinate incident response and postmortems, and drive structural fixes that reduce operational load and risk.
- Infuse AI into how the team builds and operates: evaluate and adopt AI-enhanced tooling and help define best practices.
- Mentor and level up other engineers through design/code reviews, pairing, and technical guidance.
- Collaborate closely with partner teams (Identity, Data Foundation, Activations Fullstack, Integrations/OPI) to deliver end-to-end improvements in activation reliability, speed, and observability.
You will work with talented, collaborative people in a hybrid environment with flexible paid time off, paid holidays, options for working from home, and paid parental leave. LiveRamp offers a comprehensive benefits package including medical, dental, vision, life and disability insurance, an employee assistance program, and a 401K matching plan (1:1 match up to 6% of salary).
REQUIREMENTS:
- 5+ years of experience writing and deploying high-quality production code in a modern language (Java, Go, Scala, or similar), including owning complex systems in production.
- Led the design and delivery of large-scale distributed or big data systems with clear business impact (e.g., major latency/cost improvements, substantial reliability gains, or large new capabilities).
- Strong data engineering and SQL skills: comfortable modeling data, writing and optimizing complex queries on very large tables, and reasoning about performance, correctness, and cost.
- Deep experience owning end-to-end data pipelines: ingestion, transformation, orchestration, failure handling, and observability, not just individual jobs or microservices.
- Comfortable working in a cloud environment (ideally GCP) and with containerized workloads (Kubernetes/GKE or similar); understanding how infra choices impact performance, cost, and reliability.
- Able to define and drive technical strategy: break down multi-quarter problems, evaluate tradeoffs, align stakeholders, and deliver incremental value along the way.
- Excellent communication and collaboration skills; ability to influence across teams and disciplines and drive consensus on complex technical decisions.
- Demonstrated ability to mentor and grow other engineers, give effective feedback, and create space for others to contribute.
- Comfortable with ambiguity and deeply inquisitive: ask "why" and "what if" and convert those questions into concrete experiments and system changes.
- AI-enabled development experience, or strong excitement to learn and grow in using AI-enhanced development tools (code assistants, agents for log/metrics analysis, AI-supported design and review) and help others use them effectively.
PREFERRED SKILLS:
- Google Cloud Platform (GCP): GCS, Dataproc, GKE, Pub/Sub, BigQuery, IAM.
- Workflow orchestration: Temporal or Cadence; Airflow or similar systems for long-running, failure-prone workflows.
- Apache Spark (or Dataproc) for large-scale batch processing.
- Experience with data warehouses such as SingleStore, BigQuery, Snowflake, or similar.
- Streaming systems: Kafka/Redpanda, Pub/Sub, or equivalent event/streaming platforms, especially for high-volume or incremental data processing.
- Experience designing multi-tenant systems that enforce rate limits, fairness, and SLAs across many customers and destinations.
- Strong background in performance and cost optimization for large-scale data workloads (e.g., 10–100x speedups, significant compute cost reductions).
- Prior experience working on advertising, marketing, or data activation platforms or other systems where data correctness, timeliness, and scale are all critical.
