Data Engineer

Key Skills

Apache Hadoop, C Programming, C++, Data science techniques, Java Programming, Machine learning techniques, MapReduce, Python Programming, PyTorch, R Programming, Scala Programming, SQL, TensorFlow

Job Description

To be the best science company in the world, we need more than scientists. We need passionate people who are the best at finance, human resources, law, logistics, and so much more. While we’re deeply rooted in science, DuPont careers span a wide range of skills and disciplines. Our teams are focused on achieving the best results for our customers and the business. They're inspired by innovation, excited by collaboration, and strive to achieve more agile ways of moving the business forward. Learn more about us here: https://www.dupont.com

The data scientist/engineer will work with DuPont manufacture teams and Continuous Improvement teams. They are going to be part of a project team to develop an end-to-end solution for manufacture operators to enhance or improve their operation efficiency and effectiveness by optimize the process monitoring, prediction and decrease failure rate. In a data scientist role, you will be responsible for modeling complex manufacturing process problems, discovering insights and identifying opportunities through the use of statistical, machine learning, mining and visualization techniques.

Data Engineer(Regular Employee)

The data scientist/engineer will work with DuPont manufacture teams and Continuous Improvement teams. They are going to be part of a project team to develop an end-to-end solution for manufacture operators to enhance or improve their operation efficiency and effectiveness by optimize the process monitoring, prediction and decrease failure rate.

In a data engineer role, you will assist on data retrieval from manufacturing data management platform, data process and cleaning. You will be responsible for constructing automatic data pipelines and dashboard, and deploy analytics models for data visualization and analytics.

Responsibilities:

• Collaborate with stakeholders to identify the business requirements, formulate lists of questions in analytics terms, and the expected outcome;
• Identify and select relevant and credible data sources, and provide technical instructions to data analysts to collect, integrate and mine data;
• Identify and analyze patterns. test hypotheses, and build models;
• Conducts advanced data analysis and complex algorithm to help stakeholders to discover and quantify leading information.
• Solves stakeholders’ problems through analytics and communicate results and methodologies through an iterative collaboration process.
• Partner with stakeholders to ensure the expected qualification and assurance of the information.
• Design and participate in implementation of analytics pipelines and visualization by collaborating with other digital/site team members.

Skill Requirements

General Requirement

• A college degree or higher in Engineering and/or Science.
• 2 + year experience in data analytics and data pipelines.
• Strong coding skills in Python and/or R, including data processing, statistics, ML, and visualization.
• Quick self-learner to understand the manufacture process and engineering mechanism.
• Excellent communication and customer-facing skills with the ability to explain technical approaches and rationale of findings in easy-to-understand terms to scientists, engineering, and business developers.
• Excellent team player
• Japanese and English skills with business level are mandatory

Data Engineer Specific Requirement

• Expertise in development of APIs, web services and visualization in Python, React, and PowerBI.
• Expertise in Microsoft Azure Cloud PaaS development (Azure data lake gen 2, Databricks, MS SQL, Data Factory, ML Service, etc)
• Experience in agile software engineering cycle.

Preferred but not required skill

• Proficiency in data retrieval and management in manufacturing data platforms, e.g. AspenTech IP21, SAP, and TrakSYS.
• Experience in construction of manufacturing data pipeline.
• Knowledge on statistics and machine learning.