Manufacturing Data Engineer, Technical Infrastructure, Platforms Technical Operations

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Job Overview

The Manufacturing Data Engineer in Technical Infrastructure at Google will play a crucial role in enhancing our platforms and operational efficiency through the analysis, management, and deployment of data solutions. This individual will collaborate with cross-functional teams to gather, process, and analyze large datasets, ensuring the accurate tracking of manufacturing processes and performance. The ideal candidate will apply their technical expertise to innovate and optimize reporting tools and methodologies, contributing significantly to the overall success of the organization.

Job Responsibilities

• Design, develop, and implement data pipelines to support manufacturing analytics.
• Collaborate with operations teams to identify key data requirements and ensure data integrity.
• Build dashboards and reporting tools for real-time performance monitoring and decision-making.
• Perform data analysis to find patterns and insights that impact operational efficiency.
• Enhance existing manufacturing data infrastructure to accommodate growth and changing business needs.
• Conduct regular audits of data quality and develop strategies to improve overall data governance.
• Work with data scientists and analysts to develop predictive models and analytics frameworks.
• Provide technical support and troubleshooting for data-related issues within the manufacturing processes.

Qualifications

• Bachelor’s degree in Computer Science, Engineering, or a related field; Master’s degree preferred.
• 3+ years of experience in data engineering, data analysis, or related fields, preferably in a manufacturing environment.
• Proficiency in programming languages such as Python, Java, or SQL for data manipulation and analysis.
• Strong experience with data warehousing solutions, ETL processes, and reporting tools.
• Experience with cloud platforms such as Google Cloud Platform, AWS, or Azure.
• Familiarity with big data technologies, such as Hadoop, Spark, or similar frameworks.
• Excellent analytical and problem-solving skills with attention to detail.
• Strong communication skills and ability to work collaboratively with various teams.

Technologies & Tools

This position requires proficiency with various technologies and tools essential for data engineering. Key technologies may include databases like MySQL and NoSQL solutions, data processing frameworks such as Apache Spark, ETL tools for data integration, and cloud services on Google Cloud Platform. Additionally, version control systems such as Git and project management tools like JIRA may also be utilized to streamline workflows and enhance collaboration within teams.

Ideal Candidates

An ideal candidate for the Manufacturing Data Engineer role will demonstrate a blend of technical acumen and analytical prowess, with a keen ability to translate data into actionable insights. They should possess a proactive mindset, able to foresee potential challenges and implement innovative solutions. Strong interpersonal skills are crucial, as the role involves extensive collaboration with diverse teams. The candidate should also be adaptable, thriving in a fast-paced environment while maintaining a focus on continuous improvement within data operations.