Senior Data Engineer & Scientist

Be a part of our mission! As a world leader in creating comfortable, sustainable, and efficient climate solutions for buildings, homes and transportation, it's our responsibility to put the planet first. For us at Trane Technologies, and through our businesses including Trane® and Thermo King, sustainability is not just how we do business—it is our business. Do you dare to look at the world's challenges and see impactful possibilities?

Do you want to contribute to making a better future? If the answer is yes, we invite you to consider joining us in boldly challenging what's possible for a sustainable world.

Learn about our benefits designed for you to Thrive at work and at home.

We boldly go.

Where is the work:

About the role

As a Senior Data Scientist focused on data engineering, you will discover, connect, transform, and operationalize engineering data and knowledge so that it can be reliably used by downstream AI systems, applications, and engineering workflows.

You will work across distributed data sources, structured and unstructured content, metadata, lineage, quality, cloud data services, and reusable headless data capabilities. You will help make engineering data discoverable, trustworthy, and ready for retrieval and agent use.

What you will do

• Discover engineering data and knowledge sources across distributed systems and repositories.

• Build data-ingestion, and integration pipelines.

• Connect structured and unstructured engineering data.

• Implement metadata, cataloging, lineage, and discoverability capabilities.

• Establish data quality, validation, and observability practices.

• Implement GCP or comparable cloud data platform services.

• Design interfaces for downstream AI systems and applications.

• Prepare data and knowledge for retrieval and agent use.

• Support graphs, entities, and relationship modeling.

• Build reusable headless data services.

• Use Git Hub workflows, CI/CD, Terraform, and automated testing.

• Prepare requirements, specifications, constitutions, contracts, context, and AI harnesses.

• Implement security, access control, privacy, and governance controls.

• Deploy and support production data services.

• Use Terraform for infrastructure provisioning and repeatable environment management.

Required qualifications

• Bachelor’s degree in data engineering, computer science, engineering, or related field. Master’s degree preferred.

• Two to five years of relevant experience is acceptable.

• Experience discovering and integrating distributed data sources.

• Experience with structured and unstructured engineering data.

• Experience with metadata, cataloging, lineage, and discoverability.

• Experience with data quality, validation, and observability.

• GCP or comparable cloud data-platform experience.

• Experience preparing data and knowledge for retrieval and agent use.

• Experience with graph, entity, and relationship modeling.

• Experience building reusable headless data services.

• Experience with Git Hub workflows, CI/CD, and automated testing.

• Experience with requirements, specifications, constitutions, contracts, and AI harnesses.

• Experience with security, access control, privacy, and governance.

• Production deployment and operational-support experience.

What success looks like

• You discover and connect priority engineering data and knowledge sources.

• You deliver reliable ingestion, integration, transformation, and validation pipelines.

• You improve metadata, lineage, discoverability, and operational observability.

• You prepare data and knowledge for retrieval, agent use, and downstream applications.

• You establish repeatable Terraform, Git Hub, testing, and deployment practices.

• Your work delivers measurable value for…