Data Engineer, Measured Work

Minimum Qualifications:

• Bachelor's degree in Computer Science, Mathematics, a related field, or equivalent practical experience.
• 3 years of experience coding in one or more programming languages.
• 3 years of experience working with data infrastructure and data models by performing exploratory queries and scripts.
• 3 years of experience designing data pipelines, and dimensional data modeling for synch and asynch system integration and implementation using internal (e.g., Flume, etc.) and external stacks (DataFlow, Spark, etc.).

Preferred Qualifications:

• Experience managing cross-functional projects involving multiple stakeholders, tight timelines and changing circumstances.
• Experience with collaborative coding and version control and operating in an environment where everyone’s output is peer-reviewed and feedback is addressed constructively.
• Experience with data engineering and data governance tools and technologies, including cloud platforms (e.g., GCP), data warehousing solutions, data quality tools, and metadata management systems.
• Experience with Data Center Technology or Supply Chain.

About The Job

As a Data Engineer in Measured Work, you will help in defining accurate standards of execution duration for every activity that is happening on the data-center floor and help predict accurate headcount for the given demand. You will be defining metrics that ensure operational visibility and promote accountability. You will be defining a framework to surface best practices and promote their adoption. You will be building tools that help regional VPs and Directors to data center technicians on the floor to interpret data and make short- and long-term decisions.

You will be building systems and mechanisms to obtain, process, analyze and interpret large volumes of data to help solve a problem for Google's cloud business operations. You will be partnering with our customers in and outside of our organization to build tools that provide insights into the data center floor.The AI and Infrastructure team works on the world’s toughest problems, redefining what’s possible and the possible easy. We empower Google customers by delivering AI and Infrastructure at unparalleled scale, efficiency, reliability and velocity. Our customers include Googlers, Googler Cloud customers, and billions of Google users worldwide. We’re at the center of amazing work at Google by being the “flywheel” that enables our advanced AI models, delivers computing power across global services, and offers platforms that developers use to build services.

In AI and Infrastructure, we shape the future of hyperscale computing by inventing and creating world-leading future technology, and drive global impact by contributing to Google infrastructure, from software to hardware (including building Vertex AI for Google Cloud). We work on technologies at a global scale with key players in the AI and systems space. Join a team of talented individuals who not only work together to keep data centers operating efficiently but also create a legacy of driving innovation by building some of the most complex systems technologies.

Responsibilities

• Design, develop and maintain scalable and reliable data pipelines with robust data quality checks, monitoring systems, and data lineage tracking while advocating best practices to ensure compliant data infrastructure that serves the business.
• Write data queries and drive preliminary data analysis utilizing relevant tools, leveraging custom data infrastructure or existing data models.
• Partner with stakeholders to solve problems through data-driven actionable technical designs, lead technical design reviews and collaborate with cross-functional teams, and productionize internal BI platform workflows.
• Design, develop and productionize insightful dashboards and reports that effectively communicate technical concepts and drive data-driven recommendations to audiences.
• Influence future Data Engineering strategy and contribute to scaling of Data Engineering function within the organization as the first Data Engineer hire.