Data Engineer, Data Architecture and Engineering, gDATA

gTech Ads is responsible for all support and media and technical services for customers big and small across our entire Ad products stack. We help our customers get the most out of our Ad and Publisher products and guide them when they need help. We provide a range of services from enabling better self help and in-product support, to providing better support through interactions, setting up accounts and implementing ad campaigns, and providing media solutions for customers business and marketing needs and providing complex technical and measurement solutions along with consultative support for our large customers. These solutions range from bespoke and customized ones for our customers to scalable support for millions of customers worldwide. Based on the evolving needs of our ads customers, we partner with Sales, Product and Engineering teams within Google to develop better solutions, tools, and services to improve our products and enhance our client experience. As a cross-functional and global team, we ensure our customers get the best return on investment with Google and we remain a trusted partner.

The Data, Architecture, Tools and Analytics (gDATA) team supports the gTech Ads organization. gDATA manages and utilizes large data sets to solve difficult, non-routine analysis problems while also providing operational analytics and reporting. The team combines investigative excellence, objectivity and an understanding of business strategies and operations to enable gTech and the Ads ecosystem business to drive smart business decisions.

Responsibilities

• Acquire deep understanding of business processes, tools and customer expectations, to drive greater impact.
• Design, implement, test, optimize and troubleshoot analytics and reporting solutions to solve business performance management challenges.
• Collaborate with and influence business and engineering stakeholders to ensure our data infrastructure and products meets constantly evolving requirements.
• Work closely with analysts to productionize analytics and reporting prototypes, and various statistical and machine learning models.
• Write and review technical documents, including design, requirements, and process documentation.

Minimum qualifications:

• Bachelor's degree in Computer Science, Mathematics, a related field, or equivalent practical experience.
• 1 year 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 in technical consulting.
• 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 architecting, developing software, or internet scale production-grade Big Data solutions in virtualized environments.