Lead Data Engineer, Machine Learning Operations

4 weeks ago

Hartford, Connecticut, United States Travelers Insurance Full time
Job Summary

We are seeking a highly skilled Data Engineering Lead to join our Machine Learning Operations team. As a key member of our team, you will be responsible for leading and owning the MLOps initiatives within Business Insurance Analytics and Research to accelerate model lifecycle.

This role requires a strong understanding of data engineering principles, machine learning concepts, and cloud platforms. You will work closely with cross-functional teams to design, develop, and deploy scalable and efficient data solutions.

Key Responsibilities:

  • Incorporate data quality assurance processes into ML Ops
  • Define and build ML Ops frameworks for data solutions that can be applied to multiple projects
  • Incorporate core data management competencies including data governance, data security, and data quality
  • Collaborate and build consensus with leadership and diverse groups of stakeholders in defining, estimating, prioritizing, and planning of projects
  • Define standards and frameworks for testing on data movement and transformation code and data components

Requirements:

  • Bachelor's degree in a STEM-related field or equivalent
  • Seven years of data engineering or equivalent experience
  • Expert knowledge of tools, techniques, and manipulation including cloud platforms, programming languages, and modern software engineering practices
  • Excellent delivery skills with the ability to examine and assess the effectiveness of software design strategies and methodologies
  • Demonstrated track record of domain expertise including the ability to improve company-level capabilities within the domain

What We Offer:

  • Competitive salary and benefits package
  • Opportunities for professional growth and development
  • A collaborative and dynamic work environment

Travelers is an equal opportunity employer and welcomes applications from diverse candidates. We are committed to creating an inclusive workplace where everyone feels valued, respected, and empowered to contribute their best work.

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