Senior Data Engineer, Trust and Safety, Technology and Data Enablement

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 will drive technical solutions that help Google comply with global content regulations and protect user safety. In this role, you will take ownership of design and development initiatives for our data products and infrastructure. You will solve complex and ambiguous data problems. By building a unified data architecture, you will help reduce fragmentation and ensure consistent reporting. You will collaborate closely with policy leaders and engineering partners, defining data standards and guiding our technical roadmap to scale operations effectively. As a Data Engineer, you will drive technical solutions that help Google comply with global content regulations and protect user safety. In this role, you will take ownership of design and development initiatives for our data products and infrastructure. You will solve complex and ambiguous data problems. By building a unified data architecture, you will help reduce fragmentation and ensure consistent reporting. You will collaborate closely with policy leaders and engineering partners, defining data standards and guiding our technical roadmap to scale operations effectively. Individual pay is determined by factors including job-related skills, experience, and relevant education or training. US: $156000 - $226000 (USD) + 15% bonus target + equity + benefits Learn more about benefits at Google .

Design, build, and maintain data processing systems and data structures that handle legal content removal and compliance reporting. Collaborate with policy specialists and cross-functional partners to understand business needs and translate them into robust technical data designs. Create unified data pipelines and models to simplify data access, reduce duplication, and establish clear sources of truth. Analyze and profile large datasets to uncover trends, improve data quality, and enable data-driven operational decisions. Guide engineering best practices for data life-cycle management, storage design, and data discoverability.

Minimum qualifications: Bachelor's degree in Computer Science, Mathematics, a related field, or equivalent practical experience. 5 years of experience writing software in SQL or Python. Experience working with Data Modeling, Data Storage, or Data Management. Preferred qualifications: Experience architecting, developing software, or internet scale production-grade Big Data solutions in virtualized environments. Experience designing, building, and operating data processing systems that handle high volumes of transactional records. Experience integrating disparate, legacy database systems to construct a unified source of truth for organizational reporting. Experience collaborating with non-engineering teams to understand their operational workflows and translate business needs into technical data solutions. Experience utilizing business intelligence and visualization tools to transform raw datasets into clear dashboards that support executive decision-making.