Data Analyst

About Advanced Energy

Advanced Energy Industries, Inc. (NASDAQ: AEIS) is a leading provider of precision power and control technologies that support pioneering advancements in semiconductor and industrial manufacturing. With a rich legacy and award-winning innovations, Advanced Energy fosters strong partnerships and values the unique skills and contributions of its employees globally.

Position Overview

The Data Analyst will be instrumental in promoting data-driven decision-making within quality assurance and manufacturing operations. This role involves exploring and cleaning data, performing statistical evaluations, creating analytical and predictive models, and developing visual dashboards that aid in predicting failures and driving continuous improvement efforts. Experience with data engineering such as ETL processes and database optimization is an asset but not mandatory. The ideal candidate excels at analytics and can handle structured and unstructured data from diverse factory systems.

Responsibilities

• Lead discovery meetings with business teams to grasp operational workflows, data requirements, and problem definitions, documenting both data and process flows meticulously.
• Gather, cleanse, and analyze extensive datasets from production systems including RMA, testing, SPC, and MES.
• Conduct statistical and trend analyses along with correlation assessments to uncover patterns and determine root causes.
• Develop analytical and predictive models such as anomaly detection and failure pattern recognition.
• Enable predictive quality strategies by providing data-driven insights and model support.
• Collaborate with engineering, test, and MQE teams to translate business challenges into detailed analytical needs.
• Create user-friendly dashboards and visual reports utilizing Power BI, Tableau, or related tools.
• Communicate findings and summaries effectively to stakeholders, ensuring clarity and actionable insights.

Requirements and Qualifications

• Between 2 to 5 years in a data analyst or comparable analytical role.
• Background in manufacturing, operations, or quality data analysis is beneficial.
• Preferred but not required experience in data engineering or pipeline development.
• Participation in machine learning or predictive analytics endeavors is advantageous.
• Proven ability to engage with senior business stakeholders effectively.
• Familiarity with ETL/ELT tools and workflow orchestration platforms.
• Knowledge of data engineering concepts including data pipelines and modeling.
• Exposure to big data frameworks such as Spark and Hadoop, or cloud analytics platforms like Azure and Databricks.
• Experience with project documentation tools including Jira and Confluence.
• Understanding of SAP S4 data structures is a plus.
• Hands-on experience with automation tools like Power Apps, Power Automate, and UiPath.
• Strong analytical thinking and problem-solving capabilities.
• Proficiency in Python or R for comprehensive data analysis.
• Advanced SQL skills for data querying and manipulation.
• Expertise in developing dashboards with Power BI, Tableau, or similar visualization software.
• Knowledgeable in statistical techniques and predictive modeling methodologies.
• Ability to clearly convey complex analytical insights to non-technical audiences.
• Excellent documentation and organizational skills.
• A collaborative approach to cross-functional teamwork involving engineering and operations units.

Preferred Education

Bachelor’s degree in Data Science, Computer Science, Statistics, Engineering, Information Systems, or a related discipline.

Additional Information

Advanced Energy values competitive compensation and comprehensive benefits to attract and retain a skilled, engaged workforce. Their pay practices emphasize fairness and market-based base salary combined with an annual performance incentive plan. They uphold diversity and equal employment opportunities for minorities, females, protected veterans, and individuals with disabilities. The company also adheres strictly to data privacy standards relevant to application handling.