About the role
The Data Engineer (AVP/Manager) leads the design and implementation of scalable data architectures and pipelines within a high-tech manufacturing environment. This role focuses on integrating complex datasets from manufacturing execution systems and sensors to drive yield optimization and advanced analytics.
BankingOnsite
Key Responsibilities
- Design and maintain scalable data pipelines and architectures for high-volume manufacturing data
- Collaborate with process engineers and data scientists to identify data requirements for yield improvement and predictive maintenance
- Lead a team of data engineers in developing and deploying ETL/ELT processes using SQL and Python
- Integrate data from various sources including MES, SECS/GEM, and industrial sensors into centralized data warehouses
- Optimize database performance and ensure data integrity across production and R&D environments
- Implement data governance and security protocols in compliance with industry standards
- Provide technical leadership and mentorship to junior engineering staff
- Drive the adoption of modern data stack tools such as Spark, Snowflake, or Databricks
- Translate complex technical data requirements into actionable insights for business stakeholders
Requirements
- Bachelor's or Master's degree in Computer Science, Data Science, or a related engineering field
- Minimum 8 years of experience in data engineering with at least 2 years in a leadership or managerial capacity
- Proficiency in SQL and programming languages such as Python, Scala, or Java
- Extensive experience with Big Data technologies like Hadoop, Spark, or Kafka
- Strong understanding of ETL/ELT design patterns and data modeling such as Star or Snowflake schemas
- Experience with cloud platforms including AWS, Azure, or GCP and their managed data services
- Familiarity with manufacturing systems such as MES, SPC, and yield management systems
- Proven track record of managing technical teams or leading large-scale data infrastructure projects
- Knowledge of CI/CD practices and version control using Git
- Excellent communication skills for collaborating across engineering and business units