Senior Data Engineer

What you’ll do:

Eaton Corporation’s Center for Intelligent Power has an opening for a Senior Engineer- Machine Learning Engineering. The ideal candidate will be responsible for end to end engineering, deployment, monitoring and maintaining the machine learning model at scale. This position requires understanding in machine learning and software engineering. The candidate will work closely with other teams to make sure the requested features by the businesses are delivered.

About Eaton:

Eaton is power management company with 2018 sales of $21.6 billion. We make what matters work. Everywhere you look—from the technology and machinery that surrounds us, to the critical services and infrastructure that we depend on every day—you’ll find one thing in common. It all relies on power. That’s why Eaton is dedicated to improving people’s lives and the environment with power management technologies that are more reliable, efficient, safe and sustainable. Because this is what matters. We are confident we can deliver on this promise because of the attributes that our employees embody. We’re ethical, passionate, accountable, efficient, transparent, and we’re committed to learning. These values enable us to tackle some of the toughest challenges on the planet, never losing sight of what matters.

Develop and maintain Data Engineering pipelines, continuous integration, and deployment (CI/CD) pipelines for machine learning models.

Understanding the challenges in productionizing machine learning software and collaborating with data scientists to ensure that the software best practices, templates and other ML principles are integrated to reduce cycle time.

Develop and maintain documentation and training materials for machine learning solutions.

Keep up to date with emerging technologies and trends in data engineering and cloud infrastructure.

Qualifications:

Required: Bachelor’s degree in Electronics/Electrical/Computer Science Engineering from accredited institution

Desired: Master’s degree in Electrical/Computer/Electronics & Telecomm Engineering from accredited institution

Required

Minimum 5 years’ professional experience in data engineering.

Skills:

Required:

Experience with cloud infrastructure such as AWS, Azure, or GCP.

Experience with writing data engineering pipeline code with coding best practices.

Solid proficiency of SQL and relational databases as well as non-relational (NoSQL, time-series) database systems

Proven hands-on experience in Python

Experience with CI/CD pipelines and containerization technologies such as Docker and Kubernetes.

Experience building APIs to support data consumption needs of other roles

Strong understanding of software engineering best practices, including version control, testing, and deployment.

Strong analytical and problem-solving skills.

Excellent communication skills and ability to work collaboratively with other teams.

Ability to manage multiple projects and priorities in a fast-paced environment.

Desired Expertise (in one or more of the following areas):

Experience with big data technologies such as Hadoop, Spark, or Kafka.

Familiarity with DevOps practices and tools.

Excellent verbal and written communication skills including the ability to effectively explain technical solutions as a part of virtual and global teams

Good interpersonal, negotiation and conflict resolution skills

Problem solving skills- Self-directed and drive to learn – a person, who with time in his/her hands, will independently find interesting ways to push the envelope while learning new skills and growing Self and the team.

Team player- we work in small, fast moving teams.