Staff Data Engineer, Trust and Safety Tech and Data Enablement

Google; Austin (TX); Presencial; USD 186.000 - 269.000; Jornada completa

Descripción de la vacante

Google LLC is seeking a Staff Data Engineer to support LCPS within Google Cloud Consulting Professional Services. You will lead cross-organizational work to define data sources, validation standards, and scalable data frameworks, while architecting secure data processing systems for AI-ready data infrastructure.

You will guide the creation of data models and pipelines, deploy ML models with continuous training, and ensure a unified data landscape through a Single Source of Truth.

Formación

• Bachelor's degree in Computer Science, Mathematics, or related field or equivalent practical experience.
• 10+ years of experience with Python, R, SQL for large datasets.
• 10+ years of experience with data processing software and algorithms (Hadoop, Spark, Pig, Hive; MapReduce, Flume).
• Experience leading client-facing projects with cross-functional teams.

Responsabilidades

• Lead consultations with cross-organizational partners to define data sources and validation standards, collaborating with engineers and data scientists on ML training needs
• Oversee development of infrastructure and business solutions to scale common frameworks
• Architect secure data processing systems and advocate for best practices
• Direct creation and scaling of data models, pipelines, and exchange formats to reduce data fragmentation and improve data discoverability
• Leverage and deploy ML models, including continuous training; implement new storage and serving systems to 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
• Integrate legacy systems into a unified Single Source of Truth

Conocimientos

Python

R

SQL

Data modeling

Data profiling

Cross-functional collaboration

ML training

Educación

Bachelor's degree in Computer Science, Mathematics, or related field

Herramientas

Hadoop

Spark

Pig

Hive

MapReduce

Flume

MySQL

Data Lakes

Data Warehouses

Data Mesh

Descripción del empleo

Staff Data Engineer role supporting Legal Content Policy and Standards (LCPS) through Google Cloud Consulting Professional Services, building foundational, AI-ready data infrastructure.

Responsibilities

• Lead consultations with cross-organizational partners to define data sources and validation standards, collaborating with engineers and data scientists on ML training needs
• Oversee development of infrastructure and business solutions to scale common frameworks
• Architect secure data processing systems and advocate for best practices
• Direct creation and scaling of data models, pipelines, and exchange formats to reduce data fragmentation and improve data discoverability
• Leverage and deploy ML models, including continuous training; implement new storage and serving systems to 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
• Integrate legacy systems into a unified Single Source of Truth

Requirements

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

Technologies

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

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, predictable data models
• Experience designing and implementing complex ETL pipelines for synchronous and asynchronous system integration
• Experience designing, evaluating, and managing scalable data storage and processing ecosystems (e.g., Data Lakes, Data Warehouses, Data Mesh)

Location: Austin, TX (onsite)

Salary: USD 186,000 - 269,000 per year