The Opportunity
We're seeking an experienced Analytics Data Engineer to design, build, and maintain scalable data pipelines and infrastructure. You'll work closely with data scientists, analysts, and cross-functional teams to ensure data accessibility, integrity, and performance, supporting advanced analytics and business intelligence initiatives.
Your Role and Responsibilities
Data Pipeline Development & Management :
- Design, implement, and maintain scalable data pipelines to process and integrate data from a variety of sources (e.g., sensors, production systems, chemical processes).
- Optimize data ingestion, transformation, and storage to ensure high-quality data is available for real-time and batch analysis.
Data Architecture :
Develop and optimize data models, database schemas, and storage solutions to support complex data analytics and reporting needs.Collaborate with IT and cloud infrastructure teams to ensure scalable, reliable, and secure data storage and processing environments (e.g., cloud platforms like AWS, Azure, or GCP).Collaboration with Cross-Functional Teams :
Work closely with data scientists, process engineers, and R&D teams to understand business needs and translate them into technical data solutions.Provide clean, well-documented datasets to facilitate data analysis and machine learning applications in the semiconductor cleaning process.Data Quality Assurance :
Monitor and enforce data quality standards across pipelines and storage to ensure consistency, accuracy, and completeness.Implement validation, cleansing, and error-checking mechanisms to improve data integrity and trend identification.Automation & Monitoring :
Automate recurring data processes, tasks, and reports to improve efficiency and accuracy.Develop dashboards and monitoring tools for real-time tracking of data flows and key performance indicators (KPIs).Data Security & Compliance :
Ensure data security and compliance with industry standards and regulations.Work with IT security teams to safeguard sensitive data throughout its lifecycle.Innovation & Continuous Improvement :
Stay up to date with emerging trends in data engineering, and chemical cleaning processes.Contribute to process improvements and the adoption of new technologies to enhance the company's data capabilities.Your Skills & Experience Requirements
Education : Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or a related field.Experience : 3 years of experience as a Data Engineer, Data Architect, or in a similar role, preferably in the semiconductor, chemical processing, or manufacturing industries.Technical Expertise :Proficient in data engineering tools and languages such as SQL, Python, Apache Spark, and ETL frameworks.
Experience with cloud platforms (AWS, GCP, Azure) and big data technologies.Strong understanding of relational and non-relational databases (e.g., PostgreSQL, MySQL, NoSQL).Familiarity with data warehousing, data lakes, and distributed computing concepts.Experience with containerization technologies such as Docker or Kubernetes is a plus.Industry Knowledge : Familiarity with, semiconductor, chemical cleaning solutions, and industrial automation is highly desirable.Data Visualization & Reporting : Experience with data visualization tools such as Power BI, Tableau, or like create actionable insights and reports.Problem Solving & Critical Thinking : Strong analytical skills, with the ability to identify and address data-related challenges in a fast-paced, high-tech environment.Communication Skills : Ability to communicate complex technical concepts to non-technical stakeholders, both verbally and in writing.Position Reports To :
Cleans Engineering ManagerTypical Work Hours / Schedule / Location / Travel time
Day or swing positionWork location; Oregon5 % travel time expectedPhysical Demands
Sit approximately 50% of the day creating batch recipes / analyzing data and engineering work in front of a video monitor.Daily presence on plant floor interacting with chemical operators; performing improvement direct observations, safety management, and cleanliness reviews.Occasionally observe batch charges in class 100,000 through class 100 clean areas (need safety glasses, cleanroom smocks, hard cap, etc. depending on batch charge location).Visit different areas of the manufacturing facility (e.g., functional / analytical lab, packaging area, formulation area) to coordinate experiments, observe operations, troubleshoot or verify procedure implementation.Occasional lifting up to 50 lbs.JSR is an Equal Employment Opportunity and Affirmative Action Employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender perception or identity, national origin, age, marital status, protected veteran status, or disability status.
Recruitment agencies / Headhunter do not submit resumes / CVs through our website or directly to managers. JSR will not pay fees to any third-party agency or company that does not have a signed agreement with JSR. JSR do not accept unsolicited headhunter and agency resume.
