Technical Solutions Engineer, Data Analytics

5 Months ago • 4 Years +

Devops

Full Stack Development

Job Description

This Technical Solutions Engineer role at Google Cloud focuses on providing expert support for Data Analytics products (e.g., BigQuery, AI/ML). Responsibilities include troubleshooting customer issues, determining root causes, developing diagnostic tools, and acting as a technical consultant for internal and external stakeholders. The position requires collaboration with engineering, sales, and customer teams to resolve technical deployment obstacles and ensure product readiness, availability, and scale. The role demands deep understanding of Google Cloud's Data Analytics architecture and involves working within a global 24/7 support team. Success requires strong problem-solving skills, excellent communication and the ability to advocate for customer needs within a large organization.

Good To Have:

SQL database administration experience
Open source software community experience
Cloud networking and distributed computing experience
Data warehousing, ETL, or Big Data application experience
Experience with Docker and Kubernetes

Must Have:

Bachelor's degree in STEM or equivalent experience
4+ years coding experience (Java, C, C++, .NET, Python, Shell, Perl, JavaScript)
4+ years in technical support, professional services, or software development
Troubleshooting and root cause analysis expertise
Data analytics knowledge (BigQuery, AI/ML)

Add these skills to join the top 1% applicants for this job

java

shell

javascript

kubernetes

python

perl

docker

sql

data-science

data-analytics

networking

cross-functional

problem-solving

Minimum qualifications:

Bachelor’s degree in Science, Technology, Engineering, Mathematics, or equivalent practical experience.
4 years of experience reading or debugging code in one or more of the following: Java, C, C++, .NET, Python, Shell, Perl, JavaScript.
4 years of experience in technical support, professional services, software development, or product operations management.

Preferred qualifications:

Experience with SQL database administration, open source software communities, cloud networking solutions, or distributed computing.
Experience in data analytics, warehousing, Extract Transform and Load (ETL) development, data science, or other Big Data applications.
Experience in technical consulting on database design and architecture supporting large enterprise customers with high Service Level Objective (SLO) and Service Level Agreement (SLA) requirements.
Experience working in distributed applications or micro-services in a cloud based environment (e.g., Docker, Kubernetes).
Experience working in a dynamic organization with extensive cross-collaboration across functions.

About the job

The Google Cloud team helps companies, schools, and government seamlessly make the switch to Google products and supports them along the way. You listen to the customer and swiftly problem-solve technical issues to show how our products can make businesses more productive, collaborative, and innovative. You work closely with a cross-functional team of web developers and systems administrators, not to mention a variety of both regional and international customers. Your relationships with customers are crucial in helping Google grow its cloud business and helping companies around the world innovate.

Responsibilities

Develop an understanding of Google Cloud's Data Analytics (e.g. BigQuery), AI/ML, and underlying architectures by troubleshooting, reproducing, and determining the root cause for customer reported issues, building tools, and faster diagnosis.
Act as a consultant and subject matter expert for internal stakeholders in Engineering, Sales, and customer organizations to resolve technical deployment obstacles and improve Google Cloud.
Work as a part of a team of Engineers/Consultants that globally ensure 24 hour customer support.
Understand customer issues, advocate for their needs with internal teams, including Product and Engineering teams, and drive high-quality production.
Work with customers on their production deployment to resolve issues and achieve product readiness, availability, and scale.

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