Data Engineer, Cloud Supply Chain Data Engineering

Minimum qualifications:

• Bachelor's degree in Computer Science, Information Systems, a related technical field, or equivalent practical experience.
• 3 years of experience in data analysis, database querying (e.g., SQL), and BigQuery.
• Experience in defining and implementing data governance policies, procedures, and standards.
• Experience mentoring and leading junior engineers.

Preferred qualifications:

• Experience with data analysis at scale, including statistics, and machine learning model development (e.g., data preparation, model selection, evaluation, tuning).
• Experience with a wide range of data engineering and data governance tools and technologies, including cloud platforms (e.g., Google Cloud Platform), data warehousing solutions, data quality tools, and metadata management systems.
• Experience with collaborative coding and version control.
• Proficiency in scripting languages like Python for data manipulation, analysis, and automation.
• Familiarity with data center technology or supply chain.

About the job

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.

Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.

Responsibilities

• Design, build, and maintain scalable and reliable data pipelines to ingest, process, and store data from various sources. This includes implementing robust data quality checks and monitoring systems to ensure data accuracy, integrity, and reliability.
• Write complex SQL queries for data extraction and transformation, enable both ad-hoc analysis and automated reporting. Conduct quantitative data analysis to support business decisions and identify opportunities.
• Partner with business stakeholders to understand their data needs, translate them into actionable technical designs and solutions.This includes collaborating with Engineers, Program Managers, and Product Managers.
• Create and maintain dashboards and reports to provide actionable insights to stakeholders. Effectively communicate insights and drive the implementations.
• Develop tools and systems to automate data processes, and increase overall efficiency. Proficiency in programming languages (SQL, Python), and produce readable and well-structured code.