Senior Staff Platform Engineer - Federal

Description

The Data Platform group builds high-scale, high-performance platform capabilities for data in motion and backend storage. Customers run these systems at very large volume, throughput, and concurrency.

The role is an IC5 Senior Staff Engineer position focused on distributed systems and Data Lake architecture, with a mandate to drive the next generation of platform work.

This is a flexible hybrid position requiring 2 days per week in a the company office. Offices are located in San Francisco, CA; Pleasanton, CA; Santa Clara, CA; and San Diego, CA.

The role includes support for US Regulated Markets.

Responsibilities

• Architect and build high-performance distributed systems and platform components.
• Design and build data ingestion solutions for distributed systems, with an emphasis on scalability, quality, and operational excellence.
• Write clean, modular, reusable code and enforce engineering practices, including code reviews, unit testing, automation, and design reviews.
• Build foundational libraries, frameworks, and tools that are modular, extensible, configurable, and maintainable.
• Work with other engineering teams to clarify requirements and deliver end-to-end solutions.
• Lead technical work on projects with significant complexity and risk.
• Research, evaluate, and adopt new technologies that improve platform capabilities.
• Diagnose and resolve complex production issues across distributed systems.

Requirements

• Experience using AI in engineering work, such as AI-powered coding and operations tools, workflow automation, or evaluating how AI changes the way software and infrastructure are built.
• 12+ years of hands-on engineering experience in distributed systems, data platforms, or large-scale backend infrastructure with a Bachelor's degree; or 8+ years with a Master's degree; or 6+ years with a PhD or equivalent work experience.
• Strong grasp of distributed systems architecture, design patterns, and algorithms.
• Deep Java expertise, including JVM internals, memory models, and garbage collection.
• Proven experience tuning JVM performance and profiling to find performance bottlenecks.
• Deep, hands-on experience with Helm, including chart authoring, templating, and managing overlay layering across environments.
• Strong understanding of concurrency, networking, sockets, OS internals, and performance optimization.
• Hands-on experience building and operating large-scale distributed systems.
• Experience with relational databases such as Oracle, MySQL, or PostgreSQL.
• Knowledge of security systems, methods, and protocols.
• Experience with large-scale distributed system deployments.
• Deep knowledge of replication, fault tolerance, and high-availability strategies.
• Experience working in DevOps environments to run distributed platforms in production.
• Experience with GitOps and release engineering for Kubernetes-native distributed services.
• Strong experience designing and architecting platforms with Kubernetes, covering workload deployment, upgrades, monitoring, and maintenance.
• Strong experience designing platforms with Apache Iceberg, including tables, catalogs, data encryption, schema evolution, and metadata management.
• Strong experience designing platforms with Apache Kafka, including high-scale clusters, topic and partition strategy, and high availability.
• Strong experience designing platforms with Apache Flink, including stateful stream processing and exactly-once semantics.
• Strong experience designing platforms with Apache Spark, including batch and streaming jobs, optimization, and partitioning.
• Experience with data formats such as Parquet, ORC, and Avro, and with compaction and governance strategies.
• Ability to build scalable, fault-tolerant ingestion and transformation workflows.
• Experience connecting Data Lakes with analytics engines, query services, or ML platforms.

Conditions

Base pay for this location is $181,200 - $317,100, plus equity where applicable, variable or incentive compensation, and benefits. The base pay shown is a guideline; individual total compensation varies with qualifications, skill level, competencies, and work location. Pay depends on the geographic location of the role and may change based on work location.

Work personas (flexible, remote, or required in office) are assigned based on the nature of the work and the employee's work location. To determine eligibility, the company may measure the distance between your primary residence and the nearest office using a third-party service.

The company is an equal opportunity employer.

Benefits

• Health plans, including flexible spending accounts.
• 401(k) plan with company match.
• ESPP.
• Matching donations.
• Flexible time away plan and family leave programs.