Company : Google
Google’s mission is to organize the world’s information and make it universally accessible and useful. Our company has packed a lot into a relatively young life. Since Google was founded in 1998, we’ve grown to serve millions of people around the world.
Website : www.google.com
Eligibility : Bachelor’s Degree
Experience : Freshers / Experience
Location : Hyderabad
Job Role : Data Infrastructure Engineer, Google Technical Services Ads
1. Design, develop, and support data warehouses, dashboards, and reporting tools for operational and business impact data.
2. Write extract, transform, and loads (ETL) to automate routine data collection and reporting processes using a variety of traditional as well as large-scale distributed data systems.
3. Work with Business Analysts and other non-technical business users to understand their analytical needs, document and prioritize requirements, and to help them effectively use the data and analytical tools that the team has developed.
4. Write and review end-user documentation and technical documents, including requirements and design documents for existing and future data systems.
1. Bachelor’s Degree with an emphasis on quantitative or technical work (e.g. Computer Science, Statistics, Mathematics) or equivalent practical experience.
2. Experience with relational databases including SQL queries, database definition, and schema design.
3. Experience with one or more programming languages (Python, Java, C++, etc.).
4. Experience writing and maintaining extract, transform, and load scripts (ETLs) which operate on a variety of structured and unstructured sources.
1. Experience designing data models and data warehouses.
2. Experience working with and developing for non-technical users (defining requirements, explaining technical concepts to non-technical business users, etc).
3. Experience with Unix or GNU/Linux systems including shell scripting.
4. Understanding of fundamental computing concepts including data structures and algorithms (including trees, graphs, file formats, algorithmic complexity).
5. Familiarity with non-relational data storage systems (NoSQL and distributed database management systems).
6. Strong oral and written communication skills, including the ability to communicate complex findings in a structured and clear manner to a non-technical audience.