Software Engineer, Managed Service for Apache Spark

Google; Kirkland (WA); On-site; USD 147,000 - 211,000; Full time

Benefits offered by this job

Health & dental

401(k) match

Paid time off

Sick time

Maternity leave

Baby bonding

13 holidays

Job summary

Google is hiring a Software Engineer for Managed Service for Apache Spark in Kirkland, WA. You will design and implement features to simplify Spark workloads execution, while building the Dataproc Control Plane for high availability and scalable resource management.

You will ship customer-facing features enabling Hadoop, Spark, Flink, and AI/ML workloads on Google Cloud. The role requires a solid software development background and knowledge of data structures and algorithms, with preference for

Qualifications

• Bachelor’s degree or equivalent practical experience.
• 2 years of experience with software development, or 1 year with an advanced degree.
• Master's degree or PhD in Computer Science or related fields (preferred).
• 2 years of experience with data structures and algorithms.
• Experience with Spark, YARN, Hadoop (HDFS) and Compute Engine.

Responsibilities

• Design and implement features to make Dataproc easier to use and efficient for Spark workloads.
• Architect, implement, and operate the Dataproc Control Plane for high availability and scalable resource provisioning.
• Build high-impact, customer-facing features to run Hadoop, Spark, Flink, and AI/ML in the cloud.

Skills

Software development

Mentoring

Problem solving

Education

Bachelor’s degree or equivalent

Master’s or PhD in CS or related

Tools

Apache Spark

Apache YARN

HDFS

Compute Engine

Job description

Software Engineer, Managed Service for Apache Spark

Kirkland, WA, USA

Mid

Experience driving progress, solving problems, and mentoring more junior team members; deeper expertise and applied knowledge within relevant area.

Benefits

In accordance with Washington state law, we are highlighting our comprehensive benefits package, which is available to all eligible US based employees. Benefits for this role include:

• Health, dental, vision, life, disability insurance
• Retirement Benefits: 401(k) with company match
• Paid Time Off: 20 days of vacation per year, accruing at a rate of 6.15 hours per pay period for the first five years of employment
• Sick Time: 40 hours/year (increased to 69 hours/year for Seattle) including 5 discretionary sick days per instance
• Maternity Leave (Short-Term Disability + Baby Bonding): 28-30 weeks
• Baby Bonding Leave: 18 weeks
• Holidays: 13 paid days per year

Minimum qualifications

• Bachelor’s degree or equivalent practical experience.
• 2 years of experience with software development, or 1 year of experience with an advanced degree in an industry setting.

Preferred qualifications

• Master's degree or PhD in Computer Science, or related technical fields.
• 2 years of experience with data structures and algorithms.
• Experience with Apache Spark, Apache YARN, Hadoop Distributed File System, and Compute Engine.

About the job

Google's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at massive scale, and extend well beyond web search. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to Google’s needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward.

Managed Service for Apache Spark enables open source data analytics users (Apache Hadoop, Spark, Presto, Flink, etc.) to lift and modernize their workloads into the cloud. It is a fast, easy-to-use, fully managed cloud service for running Apache Spark, Apache Hadoop and dozens of other OSS softwares in a simpler, performant and cost-efficient way. Operations that take hours or days now complete in seconds or minutes, and the customer pays only for the resources they use (with per-second billing). Managed Service for Apache Spark also easily integrates with other Google Cloud Platform (GCP) services like BigQuery, Dataplex (governance, lineage), Catalogs/Meta stores to give a powerful and complete platform for data processing, analytics, and machine learning.

Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.

The US base salary range for this full-time position is $147,000-$211,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training.

Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google.

Responsibilities

• Design and implement features that make Dataproc easier to use and and the most efficient way to run Spark workloads.
• Architect, implement, and operate the core Dataproc Control Plane, focusing on high-availability, fault-tolerance, and state management for global-scale resource provisioning and cluster orchestration.
• Build high-impact customer-facing features which make Dataproc the best place to run Hadoop, Spark, Flink, AI/ML and newer technologies in the cloud.

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