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Google

Software Engineer, Managed Service for Apache Spark

Google

Published 16 May 2026
Kirkland, WA, USA
147K - 211K USD Annual
Full Time
27500 - 275000 people

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Role Highlights

Languages used

Key skills

AI
NLP
Information Retrieval
Machine Learning
Computer Science
Open Source
Data Processing
Data Structures
System Design
Full Stack
PhD
Search
Storage
Security
UI
Cloud
Operations
Cluster

Tools, Libraries and Frameworks

GCP
Presto
Flink
BigQuery
Apache Spark
Hadoop

Description

The role involves designing and implementing features to improve the usability and efficiency of Dataproc for running Spark workloads. The engineer will architect, implement, and operate the core Dataproc Control Plane with a focus on high-availability, fault-tolerance, and state management. Responsibilities include managing global-scale resource provisioning and cluster orchestration. Additionally, the position requires building customer-facing features to support Hadoop, Spark, Flink, and AI/ML technologies in the cloud. The engineer will work on projects critical to the organization's needs while maintaining the flexibility to switch teams as the business evolves.

Required Qualifications and Skills

Candidates must possess a Bachelor's degree or equivalent practical experience. A minimum of two years of experience in software development is required, or one year of experience if the candidate holds an advanced degree. Preferred qualifications include a Master's degree or PhD in Computer Science or a related technical field. Additionally, two years of experience with data structures and algorithms is preferred.

Disclaimer

Disclaimer: Job and company description information and some of the data fields may have been generated via GPT-4 summarisation and could contain inaccuracies. The full external job listing link should always be relied on for authoritative information.

About the company

Google

Size

275773

Website

goo.gle

HQ

Mountain View, US

Public/Private

Public Company

Description

At gTech's Users and Products team, innovations are focused on enhancing user engagement and solving complex customer needs through technical expertise and a deep understanding of Google's and Alphabet's broad product environments. The team acts as a bridge between Google’s users and its product teams, ensuring that user insights are integrated into product offerings which support numerous annual product launches. The newly formed Machine Learning Data Operations (MLDO) team within gUP Operations plays a critical role in delivering and tuning machine learning and GenAI data operations across Google’s product suite, leveraging extensive global vendor networks. Google's overarching goal is to create impactful products and services, with gTech playing a strategic role in bringing these solutions to fruition through technological and operational expertise.

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