Data Analyst

Data Engineer (I) Sunnyvale, CA - 94089 6-months contract role Note: This is a Data Analyst role focused on Manufacturing Test Quality and Data Standards within Cloud Supply Chain Operations, responsible for ensuring manufacturing and test data is accurate, reliable, and standardized to support operational efficiency and data-driven decision-making. The role involves analyzing manufacturing test data to define and measure data quality standards across key quality dimensions, performing statistical analysis, and improving data consistency for both new and existing datasets. Key responsibilities include developing dashboards to monitor and visualize data quality across manufacturing partners, building automated monitoring and anomaly detection workflows, supporting log analysis and search optimization, and assisting with AI-driven initiatives such as intelligent data mapping, anomaly detection, and data quality rule recommendations. The ideal candidate should have strong SQL and scripting skills (Python/R), analytical and problem-solving abilities, and experience with BI tools, data quality/governance concepts, and exposure to machine learning or LLM-based data applications. As a Data Engineer, you execute complete, tactical tasks within the scope of a larger project with guidance from manager, team drive, or senior colleagues, within bounded time. You apply standard tools, resources, and processes to solve defined problems, and work on developing working relationships outside the team to contribute to cross-project collaborations. You possess a foundational understanding of core data and role-related knowledge, relevant to our technologies, and processes and translate business requirements/needs into technical data solutions. Responsibilities include: • Create and/or consult in creating data visualizations, visualization features using internal BI tools like PLX, Data studio, and external tools like Tableau and Looker, with some guidance. • Provide ongoing support for data users through maintenance of reports, queries, and dashboards with some guidance. • Perform exploratory data analysis and profiling utilizing relevant tools, leveraging custom data infrastructure, or existing data models with some guidance. Work with clients to understand their needs and clarify details of requirements. Enable data-driven decision-making by collecting, transforming, and publishing data. • Leverage, deploy, and continuously train pre-existing machine learning models. Learn and implement new storage/MPP systems/ML serving systems, with some guidance. • Implement business solutions and infrastructure to build and scale common frameworks for use with some guidance. Seek and follow local technical best practices, including making data discoverable, thinking about the lifecycle of data, and managing master data well. Design, build, operationalize, secure, and monitor data processing systems with a particular emphasis on security and compliance, scalability and efficiency, reliability and fidelity, and flexibility and portability. • Develop and maintain data models, pipelines, and exchange formats to assist in the visualization, analysis, interpretation of data and for use of data in ML training/models, with direct guidance. • Consult with users, partners, or decisions makers to identify data sources, required data elements, or data validation standards with some guidance. Consult with application engineers to understand and influence logging/transactional storage. Consult with Data scientists on ML training, feature engineering for ML models. Minimum role qualification requires proficiency in: • Code comprehension and programming skills • Information gathering skills • Project management • Data exploration • Big data infrastructure • Machine Learning Knowledge • Stakeholder management • Data pipeline (ETL) design and Data Modeling • Statistics & BI tools Thanks, Nandit