Google Hiring Data Infrastructure Engineer In Hyderabad


Title of Job:- Data Infrastructure Engineer, Google Technical Services

Eligibility:- Freshers/Experiance Bachelor Degree

Location:- Hyderaad,IN

Company:- Google

About Us:- Google is an American multinational technology company specializing in Internet-related services and products that include online advertising technologies, search, cloud computing, software, and hardware.

Website:- www.google.com

Job Desription:-

- Support business optimization of sales, marketing and support efforts via data mining, modeling, user segmentation and forecasting.
- Manage data and analysis requests from start to finish, including gathering data requirements, pulling and validating data, analyzing data, building statistical models, visualizing results, synthesizing insights and presenting results.
- Uses predictive modeling, statistics, Machine Learning, Data Mining, and other data analysis techniques to collect, explore, and extract insights from structure and unstructured data on finding business insights to be consumed by multiple functional teams.
- Act independently to identify and evangelize opportunities for improved analysis and efficiency through better data and analytics practices.
- Experience working on multiple projects at the same time, with short deadlines.
- Strong Business communication skills (both written & verbal).

Qualifications

- Expertise and understanding of Sales, Marketing, Channel and Customer support business processes in SW vertical is a plus
- Strong problem solving and analytical skills with the desire to apply those skills in analyzing complex business problems
- Ability to communicate complex quantitative analysis and analytic approaches in a clear, precise, and actionable manner
- Excellent Data Analytical / User interaction and Presentation Skills
- Comfort manipulating and analyzing complex, high-volume, high-dimensionality data from varying data sources and big data sources.
- Experience in statistics, data mining and predictive modeling
- Expert knowledge of a scientific computing language such as R, Python
- Experience working with data-distributed query tools (Hadoop, Hive, etc.)
- Experience with relational databases and SQL-like query languages is a must
- Hands on with various datasets/entities including Campaign, Response, Lead, Contact, Account, Partner, Opportunity, Quote, Order, Asset, Entitlement, Service Request etc is a plus
- This role is not a typical "9-5" schedule and needs coordination with onsite resources.

Responsibilities

Design, develop, and support data warehouses, dashboards, and reporting tools for operational and business impact data.
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.
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.
Write and review end-user documentation and technical documents, including requirements and design documents for existing and future data systems.
Qualifications
Minimum qualifications:
Bachelor’s degree with an emphasis on quantitative or technical work (e.g. Computer Science, Statistics, Mathematics) or equivalent practical experience.
Experience with relational databases including SQL queries, database definition, and schema design.
Experience with one or more programming languages (Python, Java, C++, etc.).
Experience writing and maintaining extract, transform, and load scripts (ETLs) which operate on a variety of structured and unstructured sources.

Preferred qualifications:

Experience designing data models and data warehouses.
Experience working with and developing for non-technical users (defining requirements, explaining technical concepts to non-technical business users, etc).
Experience with Unix or GNU/Linux systems including shell scripting.
Understanding of fundamental computing concepts including data structures and algorithms (including trees, graphs, file formats, algorithmic complexity).
Familiarity with non-relational data storage systems (NoSQL and distributed database management systems).
Strong oral and written communication skills, including the ability to communicate complex findings in a structured and clear manner to a non-technical audience.




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