Data and Tools Engineer

1 Month ago • 8 Years + • Data Analyst • $138,000 PA - $202,000 PA

Job Summary

Job Description

The Data and Tools Engineer at Google's Product Lifecycle and Technical Operations (PLaTO) will build, maintain, and improve data infrastructure, tools, and automation for data scientists, analysts, and engineers. This role focuses on integrating data from Contract Manufacturers (CMs), enabling efficient data processing and visualization within a manufacturing test context. Responsibilities include designing and implementing scalable data pipelines, developing internal tools, ensuring data reliability and performance, and collaborating with stakeholders to meet data needs. The engineer will also build data quality monitoring systems, implement data governance policies, and troubleshoot data-related issues.
Must have:
  • 8+ years data engineering experience
  • Data transformation, modeling, warehousing
  • SQL, NoSQL, data visualization tools
  • Scripting language (SQL, Python, Java, Scala)
  • Design, develop, maintain data pipelines
Good to have:
  • Experience with external partners/suppliers
  • Manufacturing data domains (MES, ERP)
  • EDI or data exchange formats
  • Cloud-based data platforms (e.g., GCP)
  • Data governance and security best practices
Perks:
  • Bonus
  • Equity
  • Benefits

Job Details

Minimum qualifications:

  • Bachelor's degree in Computer Science, Engineering, Data Science, or a related field.
  • 8 years of experience in a data engineering or similar role.
  • Experience in data transformation, modeling and warehousing concepts and techniques, and database principles (e.g., SQL and NoSQL).
  • Experience with data visualization tools (e.g., Tableau, Power BI, Looker).
  • Experience with one scripting language, such as SQL, Python, Java, or Scala.

Preferred qualifications:

  • Experience with integrating data from external partners or suppliers.
  • Experience with specific manufacturing data domains (e.g., MES, ERP).
  • Experience with EDI or other data exchange formats commonly used with external partners.
  • Experience with cloud-based data platforms and services (e.g., GCP).
  • Knowledge of data governance and security best practices, and excellent communication and collaboration skills.

About the job

Google has one of the largest and most powerful computing infrastructures in the world. Your team is responsible for providing the manufacturing capability to deliver this state-of-the-art physical infrastructure. As a Manufacturing Engineer, you evaluate the product designs and create the processes, tools and procedures behind Google's powerful search technology. When vendors build parts for our infrastructure, you're right there alongside ensuring manufacturing processes are repeatable and controlled. You collaborate with Commodity Managers and Design Engineers to determine Google's infrastructure needs and product specifications. Your work ensures the various pieces of Google's infrastructure fit together perfectly and keep our systems humming along smoothly for a seamless user experience.

Within Product Lifecycle and Technical Operations (PLaTO), we are a Central Test Engineering organization. We are seeking a talented and passionate Data and Tools Engineer to join our growing Project Management Office (PMO) team.

As a Data and Tools Engineer, you will play a crucial role in building, maintaining, and improving the data infrastructure, tools, and automation that empower our data scientists and analysts, engineers, and other stakeholders to efficiently access, process, and analyze data, particularly within our manufacturing test context. You will be responsible for designing and implementing scalable data pipelines, developing internal tools to streamline data workflows, and ensuring the reliability and performance of our data ecosystem, with a specific focus on integrating data from Contract Manufacturers (CMs) and enabling effective data processing and visualization.

Google is an engineering company at heart. We hire people with a broad set of technical skills who are ready to take on some of technology's greatest challenges and make an impact on users around the world. At Google, engineers not only revolutionize search, they routinely work on scalability and storage solutions, large-scale applications and entirely new platforms for developers around the world. From Google Ads to Chrome, Android to YouTube, social to local, Google engineers are changing the world one technological achievement after another.

The US base salary range for this full-time position is $138,000-$202,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. 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 .

Responsibilities

  • Design, develop, and maintain robust and scalable data pipelines. Ingest, transform, and load data from sources, including external Contract Manufacturers (CMs). Develop and implement processes for onboarding new CM into our data ecosystem.
  • Design and maintain efficient and well-structured backend data tables and schemas in our data warehouse and operational data stores, ensuring data integrity, performance, and ease of querying.
  • Collaborate with data scientists and analysts, engineers and other stakeholders to understand their data needs, including specific requirements for visualizing manufacturing performance, supply chain data from CMs, and key operational metrics.
  • Build and maintain internal tools and frameworks. Develop and maintain data quality monitoring and alerting systems. Implement and manage data governance policies and procedures. Document data pipelines, tools, and processes.
  • Troubleshoot and resolve data-related issues in a timely and efficient manner.

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