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Kuukausipalkka
€174 - €275
Julkaistu 27. elokuuta 2026 · 2 päivää sittenViimeksi nähty 27. elokuuta 2026Arvioitu päättymispäivä 1. lokakuuta 2026

Senior Staff Data Platform Engineer

Senior Staff Data Platform Engineer - Kafka - Apache Iceberg - Apache Spark
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Palkkayhteys: Senior Staff Data Platform Engineer

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Tietoa tehtävästä

Position Location: This is a Flexible (Hybrid) position. Flexible positions require 2 days per week in a ServiceNow office location. We have offices in several locations, including San Francisco, CA; Pleasanton, CA; Santa Clara, CA; San Diego, CA Team Overview The Data Platform group builds highly scalable, high‑performance platform capabilities for data‑in‑motion and backend storage systems. Our customers operate at massive scale, pushing the boundaries of data volume, throughput, and concurrency. We are looking for a seasoned IC5 Senior Staff Engineer with deep expertise in distributed systems, data ingestion pipelines, and Data Lake architectures to drive next‑generation platform innovation. Role Summary As an IC5 Senior Staff Engineer, you will architect and deliver large‑scale distributed platform components, lead complex technical initiatives, and define engineering best practices. You will bring strong leadership, hands-on engineering depth, and the ability to design and operate reliable, scalable, and high‑performance data systems. What you get to do in this role: Architect, design, and build high‑performance distributed systems and platform components. Build distributed systems data ingestion solutions with strong emphasis on scalability, quality, and operational excellence. Design software that is easy to use, extend, and customize for customer‑specific environments. Deliver high‑quality, clean, modular, and reusable code while enforcing engineering best practices (code reviews, unit testing, automation, design reviews). Build foundational libraries, frameworks, and tools focused on modularity, extensibility, configurability, and maintainability. Collaborate across engineering teams to refine requirements and deliver end‑to‑end solutions. Provide technical leadership for projects with significant complexity and risk. Research, evaluate, and adopt new technologies that enhance platform capabilities. Troubleshoot and diagnose complex production issues across distributed systems. Qualifications To be successful in this role you have: Experience leveraging or critically thinking about how to integrate AI into engineering work — whether using AI-powered coding and operational tooling, automating workflows, or reasoning about how AI changes the way software and infrastructure are built. 10+ years of software development experience with a Bachelors degree; OR 8+ years with a Masters degree; OR 6+ years with a PhD OR equivalent work experience. Core Distributed Systems Expertise Strong fundamentals in distributed systems architecture, design patterns, and algorithms. Deep programming expertise in Java, including JVM internals, memory models, and garbage collection. Proven experience in JVM performance tuning, profiling, and diagnosing performance bottlenecks. 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. Streaming & Messaging Systems Experience with large‑scale deployments of Kafka, or similar streaming platforms. Deep knowledge of stream processing, topic design, partitioning, replication, and HA strategies. Experience working within DevOps environments for operationalizing distributed platforms. Demonstrated experience architecting and delivering full‑stack Data Lake solutions. Strong expertise in designing and operating data ingestion pipelines using: Apache Iceberg (tables, catalogs, schema evolution, metadata management) Kafka Connect (source/sink connectors, distributed mode) Apache Kafka (high‑scale clusters, topic/partition strategies, HA) Apache Flink (stateful stream processing, exactly‑once semantics) Apache Spark (batch & streaming jobs, optimization, partitioning) Expertise in data formats such as Parquet, ORC, and Avro, along with compaction and governance strategies. Ability to build scalable, fault‑tolerant ingestion and transformation workflows. Experience integrating Data Lakes with analytics engines, query services, or ML platforms. For positions in this location, we offer a base pay of $181,200 - $317,100, plus equity (when applicable), variable/incentive compensation and benefits. Sales positions generally offer a competitive On Target Earnings (OTE) incentive compensation structure. Please note that the base pay shown is a guideline, and individual total compensation will vary based on factors such as qualifications, skill level, competencies, and work location. We also offer health plans, including flexible spending accounts, a 401(k) Plan with company match, ESPP, matching donations, a flexible time away plan and family leave programs. Compensation is based on the geographic location in which the role is located and is subject to change based on work location.

Työn tiedot

Taidot ja teknologiat

JavaJVMKafkaApache IcebergKafka ConnectApache KafkaApache FlinkApache SparkParquetORCAvro
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