Data Engineer, Google Cloud

Minimum qualifications:

• Bachelor's degree in Computer Science, Mathematics, a related field, or equivalent practical experience.
• 3 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.
• Experience with database administration techniques or data engineering, as well as writing software in Java, C++, Python, Go, or JavaScript.

Preferred qualifications:

• Experience working with data warehouses, including data warehouse technical architectures, infrastructure components, ETL/ELT, and reporting/analytic tools and environments.
• Experience working with Big Data, information retrieval, data mining, or machine learning.
• Experience in building multi-tier high availability applications with modern web technologies (e.g., NoSQL, MongoDB, SparkML, TensorFlow).
• Experience in technical consulting.
• Experience architecting, developing software, or internet scale production-grade Big Data solutions in virtualized environments.

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.

• Research and develop deep understanding of cloud data.
• Collect, aggregate, cleanse, and analyze data from various sources. Translate complex data sets into actionable insights and present them in a clear and understandable manner.
• Develop and maintain data pipelines to ensure the reliable and efficient flow of data from source systems to the analytics application and reporting tools.
• Implement data governance and security best practices to protect sensitive data and ensure compliance with relevant regulations.
• Continuously evaluate and adopt new technologies and tools to enhance the capabilities of the analytics platform and improve data management processes.