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Salary
≈ $85k – $177k per year (Estimated)
Location
In office (Austin)
Seniority
Junior · 5+ years exp

Confirmed on the employer's own hiring board on Oct 23, 2026. First seen by Alion on Oct 20, 2026. Google scores B on the Alion truth index.

Overview
Company
Impact
Profile match
Google is an American technology company founded in 1998 by Larry Page and Sergey Brin and now the principal subsidiary of Alphabet, headquartered in Mountain View, California. It operates the world's dominant search engine and the advertising system built around it, along with YouTube, Android, Chrome, Gmail, Maps, Workspace and Google Cloud, reaching billions of users across nearly every internet-connected market. The company designs its own silicon in the Tensor Processing Unit line, develops the Gemini foundation models through Google DeepMind, and derives most of its revenue from advertising while cloud has become its fastest growing segment.

About the job

The Google Cloud Consulting Professional Services team guides customers through the moments that matter most in their cloud journey to help businesses thrive. We help customers transform and evolve their business through the use of Google’s global network, web-scale data centers, and software infrastructure. As part of an innovative team in this rapidly growing business, you will help shape the future of businesses of all sizes and use technology to connect with customers, employees, and partners.

As a Data Engineer, you'll guide customers on how to ingest, store, process, analyze, explore, and visualize data on Google Cloud Platform. You will lead data migrations and transformations, partner with clients to architect scalable data processing systems, build efficient data pipelines, and resolve platform challenges. In this role, you'll collaborate with Google's strategic cloud customers and our team to successfully implement Google Cloud products.

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.

Individual pay is determined by factors including job-related skills, experience, and relevant education or training.

US: $130000 - $187000 (USD) + 15% bonus target + equity + benefits

Learn more about benefits at Google.

Responsibilities

  • Act as a trusted technical advisor to customers and solve complex Big Data and AI challenges.
  • Create and deliver best practice recommendations, tutorials, blog articles, sample code, and technical presentations, tailoring approach and messaging to varied levels of business and technical stakeholders.
  • Analyze on-premises and cloud database environments and consult on the optimal design for performance and deployment on Google Cloud Platform.
  • Travel regularly up to 30% of the time, in-region for meetings, technical reviews, and onsite delivery activities.
  • Communicate effectively via video conferencing for meetings, technical reviews, and onsite delivery activities.

Qualifications

Minimum qualifications:

  • Bachelor's degree in Computer Science, a related field, or equivalent practical experience.
  • 5 years of experience with data processing software (e.g., Spark, Beam) and algorithms.
  • Experience managing client-facing projects, troubleshooting technical issues, and working with Engineering and Sales Services teams
  • Experience with database administration techniques or data engineering, as well as writing software in Java, Python, or SQL.

Preferred qualifications:

  • Google Cloud Platform (GCP) Professional Data Engineer Certification.
  • Experience building machine learning solutions and working with technical customers.
  • Experience in technical consulting and working with data warehouses, including data warehouse technical architectures, infrastructure components, ETL/ELT, and reporting/analytic tools and environments.
  • Experience building production LLM/GenAI systems: multi-agent orchestration, agent frameworks (e.g., ADK), tool and function calling, RAG, and prompt/context development.
  • Experience architecting, developing software, or internet scale production-grade Big Data solutions in virtualized environments.
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