Join Google's Devices & Services team to make an impact on how people interact with technology. Our mission is to organize the world's information and make it universally accessible and useful. In this role, you will be at the forefront of building and maintaining data processing, machine learning, and automation software. Your contributions will solve representation, scale, and efficiency challenges, helping us create transformative user experiences.
Responsibilities
- Data Infrastructure Development. Design, build, optimize, and maintain data infrastructure, including large-scale data processing pipelines (e.g., ETL, BigQuery, Snowflake, Redshift, Dataflow, Beam, Spark Jobs), ML model training/tuning (e.g., AutoML), and orchestration workflows (e.g., Cloud Composer, Airflow, Prefect).
- Engineering Best Practices. Advocate for and implement engineering best practices within and beyond the team. Write and review technical documentation, produce highly-readable and style-conformant code, and lead training sessions.
- Policy and Governance Compliance. Ensure compliance with complex and evolving policy and governance requirements.
- Stakeholder Collaboration. Collect and analyze data from analysts, data scientists, and business stakeholders. Understand and align data initiatives with broader business priorities.
Minimum Qualifications
- Bachelor’s degree in a quantitative or technical field (e.g., Computer Science, Statistics, Mathematics, Engineering), or equivalent practical experience.
- 3 years of experience in data engineering or business intelligence roles, contributing to a shared codebase.
- 3 years of experience in system design or in a programming language (e.g., Java, C++, Python, etc.).
- Experience with relational databases, including writing and optimizing SQL queries and designing schema.
Preferred Qualifications
- Experience using SQL in large-scale investigative, NoSQL, or columnar contexts.
- Familiarity with continuous integration and deployment systems (e.g., Cloud Build, GitLab, Jenkins).
- Experience writing unit tests (e.g., PyTest, Selenium, JUnit).
- Knowledge of Machine Learning (ML) techniques and applications.
Google’s Commitment
Google is an equal opportunity workplace and an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, or veteran status. We consider qualified applicants regardless of criminal histories, consistent with legal requirements.