Cloud AI Data Engineer II — Build Scalable Data Pipelines

Google LLC; Austin, Atlanta (TX, GA); On-site; USD 156,000 - 226,000; Full time

Benefits offered by this job

Health insurance

Dental insurance

Vision insurance

Life insurance

Disability insurance

401(k) with company match

Paid time off – 20 days/year

Sick time – 40 hours/year

Maternity leave – 28–30 weeks

Baby bonding leave – 18 weeks

13 paid holidays

Job summary

Google LLC is hiring an AI Data Engineer in the US to guide customers in ingesting, storing, processing, and visualizing data on Google Cloud. You will lead data migrations, architect scalable pipelines, and collaborate with clients and internal teams to implement Google Cloud products.

Responsibilities include recommending best practices, solving complex data challenges, and delivering technical content. Travel up to 30% is required in-region.

Qualifications

• Bachelor's degree in Computer Science or related field or equivalent experience.
• At least 5 years of data processing software experience (Spark/Beam) and algorithms.
• Experience managing client-facing projects and coordinating with Engineering and Sales teams.
• Experience with database administration or data engineering and software development in Java/Python/SQL.

Responsibilities

• Act as a trusted technical advisor to customers and solve complex Big Data challenges.
• Create and deliver best practice recommendations, tutorials, and technical presentations.
• Analyze on-premises and cloud database environments for performance and deployment on Google Cloud.
• Travel regularly up to 30% for in-region meetings and onsite delivery.
• Communicate effectively via video conferencing for reviews and delivery activities.

Skills

Client-facing projects

Troubleshooting complex issues

Team collaboration

Education

Bachelor's degree in Computer Science or related field

Tools

Spark

Beam

Java

Python

SQL

Job description

Google LLC is hiring an AI Data Engineer in the US to guide customers in ingesting, storing, processing, and visualizing data on Google Cloud. You will lead data migrations, architect scalable pipelines, and collaborate with clients and internal teams to implement Google Cloud products.

Responsibilities include recommending best practices, solving complex data challenges, and delivering technical content. Travel up to 30% is required in-region.