Data Engineer, Technical Infrastructure

Minimum qualifications:• Bachelor's degree in Electrical, Process, or Manufacturing Engineering, or equivalent practical experience.• 5 years of experience in manufacturing engineering.• 2 years of experience in development of databases, ETL, SQL, Analytics, and Machine Learning.Preferred qualifications:• 3 years of experience in full-stack enterprise application development.• Experience in hardware quality and reliability domains.• Excellent communication skills.About the jobBehind everything our users see online is the architecture built by the Technical Infrastructure team to keep it running. From developing and maintaining our data centers to building the next generation of Google platforms, we make Google's product portfolio possible. We're proud to be our engineers' engineers and love voiding warranties by taking things apart so we can rebuild them. We keep our networks up and running, ensuring our users have the best and fastest experience possible.The US base salary range for this full-time position is $111,000-$163,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. The range displayed on each job posting reflects the minimum and maximum target salaries for the position across all US locations. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google .Responsibilities• Develop analytics applications to deliver on-demand and predictive insights to improve Google's data center quality.• Own data engineering workstreams, including data acquisition, data pipelining, data quality, data prep, and data warehousing.• Lead the technical delivery, implementation, and business adoption of new scalable and reliable data analytics and business intelligence solutions for cross-functional teams.• Design and implement advanced analytics, machine learning models, and rich data visualizations.• Engage stakeholders and partner teams to gain a deep understanding of business needs, and to develop innovative solutions to challenging business problems.