Staff Data Engineer, Trust and Safety Tech and Data Enablement

Google Cloud Consulting Professional Services is hiring a Staff Data Engineer for the Trust and Safety Tech and Data Enablement team, supporting the Legal Content Policy and Standards (LCPS) organization. This role focuses on building foundational, AI-ready data infrastructure that unifies disparate sources into a scalable Single Source of Truth, enabling reliable data for downstream analysis and model development.

Role Focus

The Staff Data Engineer leads the design and development of complex, scalable data pipelines and drives the integration of legacy systems into a unified data foundation. The work supports secure data processing, reduces fragmentation through standardized models and exchange formats, and improves data discoverability for the broader data engineering environment.

Responsibilities

• Lead consultations with cross-organizational partners to define data sources and validation standards, coordinating with engineers and data scientists on ML training requirements.
• Oversee infrastructure and business solutions that scale shared frameworks, including the design of secure data processing systems while promoting best practices.
• Direct the development and scaling of data models, pipelines, and exchange formats to reduce fragmentation and increase discoverability.
• Leverage and deploy ML models, continuously training models over time while implementing new storage and serving systems to support scale across Data Engineering.
• Manage data profiling and analysis using existing data models and custom infrastructure to clarify client requirements and enable data-driven decision-making.

Requirements

• Bachelor’s degree in Computer Science, Mathematics, or related field (or equivalent practical experience).
• 10 years of experience writing code using specialized languages and libraries such as Python, R, and SQL for datasets.
• 10 years of experience with data processing software including Hadoop, Spark, Pig, and Hive, and algorithms such as MapReduce and Flume.
• Experience managing client-facing projects, troubleshooting technical issues, and working with Engineering and Sales Services teams.

Preferred Qualifications

• 10 years of experience designing robust, scalable, and synchronized pipelines, including dimensional modeling.
• Experience partnering with non-technical stakeholders to translate ambiguous business or regulatory requirements into structured technical designs.
• Experience interpreting and designing data elements, structures, and relationships to deliver consistent and predictable data models, including complex ETL pipelines for synchronous and asynchronous system integration.
• Experience designing, evaluating, and managing scalable data storage and processing ecosystems such as Data Lakes, Data Warehouses, and Data Mesh.

Technologies

• Python, R, SQL
• Hadoop, Spark, Pig, Hive
• MapReduce, Flume
• MySQL
• Data Lakes, Data Warehouses, Data Mesh

Location and Compensation

• Location: Austin, TX (onsite)
• Salary Range: USD 186,000 to 269,000 per year