Software Engineer, Data Engineering, LabOS, Quantum AI
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Minimum qualifications:
- Bachelor’s degree or equivalent practical experience.
- 2 years of experience with software development in one or more programming languages, or 1 year of experience with an advanced degree.
- 2 years of experience in Data Management or Data Integration or Data Domain, System Integration, Distributed Databases, SQL Pipelines.
Preferred qualifications:
- Experience programming in Python.
- Experience in writing and maintaining Extract, Transform, Load (ETL) that operate on a range of structured and unstructured sources.
- Experience with large-scale data processing.
- Experience with modeling business processes or real-world data sources.
- Experience with setting and implementing data governance policies.
- Excellent written communication, organizational, and problem-solving skills.
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.
The Quantum AI LabOS team is devoted to developing, maintaining, integrating and productionizing software for running the quantum hardware lab. This includes supporting quantum chip design, fabrication, operation, automation, observability, and tracking.
In this role, you will help us build data-powered decision-making tools, e.g., data pipelines, data warehouse, databases, data governance, etc. You will guide users in the Quantum Hardware Lab on how to ingest, store, process, analyze, and explore/visualize data on the Google Cloud Platform. You will work on data migrations and transformational projects, and troubleshoot potential platform issues.
This role may involve working with technical information that is export-controlled. Non-US persons would require an export license to do so (US citizens, lawful permanent residents, and certain protected individuals are considered “US persons” under applicable law).
The full potential of quantum computing will be unlocked with a large-scale computer capable of complex, error-corrected computations. Google Quantum AI's mission is to build this computer and unlock solutions to classically intractable problems. Our roadmap is focused on advancing the capabilities of quantum computing and enabling meaningful applications.
The US base salary range for this full-time position is $141,000-$202,000 + 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. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.
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, develop and support data pipelines, warehouses, databases, reporting and visualization systems to solve operations and users problems, for both existing and new data, using a variety of traditional as well as large-scale distributed data systems.
- Collaborate and influence users and stakeholders to ensure our data infrastructure meets constantly evolving requirements and data governance policies.
- Work closely with research scientists and engineers to productionize analysis models using data processing pipelines. Recommend improvements and implement modifications to existing data models and ETL pipelines.
- Write and review technical documents including design, development, and revision documents. Drive innovation with new analytical tools to gain more insight from data.
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If you have a need that requires accommodation, please let us know by completing our Accommodations for Applicants form.
Google is a global company and, in order to facilitate efficient collaboration and communication globally, English proficiency is a requirement for all roles unless stated otherwise in the job posting.
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