Data Engineer
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Minimum qualifications:
- Bachelor's degree or equivalent practical experience.
- 3 years of experience in a data engineering, data infrastructure, or data analytics role.
- Experience with database administration techniques or data engineering, as well as writing software in Java, C++, Python, Go, or JavaScript.
Preferred qualifications:
- Experience with data warehouses, including data warehouse technical architectures, infrastructure components, ETL/ELT, and reporting/analytic tools and environments.
- Experience with data analysis, including statistics, and ML model development (data preparation, model selection, evaluation, tuning).
- Experience in scripting languages like Python for data manipulation, analysis, and automation.
- Ability to monitor, troubleshoot, and tune data systems and pipelines to improve efficiency.
- Ability to develop tools and systems to automate data processes, and increase overall efficiency, with proficiency in programming languages (e.g., SQL, Python), producing readable and well-structured code.
- Ability to deliver and maintain data projects from conception to production.
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. Implement robust data quality checks and monitoring systems to ensure data accuracy, integrity, and reliability.
- Write complex SQL queries for data extraction and transformation, enabling both Ad-hoc analysis and automated reporting. Conduct quantitative data analysis to support business decisions and identify opportunities for improvement.
- Develop and manage robust, scalable data foundations and models specifically designed to support AI/ML initiatives and the generation of AI-driven insights.
- Develop, test, and deploy intelligent agents using Python and the Google ADK framework to automate complex tasks, such as data analysis, report generation, and system orchestration.
- Proactively partner with executive business stakeholders, and data scientists.
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Google is a global company and, in order to facilitate efficient collaboration and communication globally, English proficiency is a requirement for all roles unless stated otherwise in the job posting.
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