Software Engineer- Data Platform

We're looking for a Software Engineer – Data Platform to join our Data Platform team and help scale the infrastructure behind Uplight's data ecosystem.

How you will make an impact:

You'll join a remote-first data platform team working on the infrastructure-as-code, enablement tooling, and platform administration that ensure teams across the company can use our Databricks platform effectively. Instead of building product pipelines, you'll contribute to the platform layer that everyone else builds upon, helping keep it reliable, secure, well governed, and easy to use.

If you like working at the overlap of cloud infrastructure and data platforms, and you want your work to support clean energy, this is a great fit.

What you get to do:

• Build and maintain Databricks infrastructure across AWS and GCP using Terraform
• Contribute to Unity Catalog administration including metastores, workspaces, catalog and schema infrastructure, and the grants and access patterns that keep data secure without slowing teams down
• Help build deployment accelerators, templates, and self-service tooling (including Databricks Asset Bundles) so other teams can onboard and ship on their own
• Support engineers across the company as they use the platform, troubleshooting issues and turning repeat questions into documentation and tooling
• Develop and maintain CI/CD pipelines in CircleCI, including OIDC authentication and service principal deployment patterns
• Maintain and iterate on our existing MLOps infrastructure
• Help bring agentic AI into the team's day-to-day workflows, using AI coding agents and assistants across development, code review, testing, and operational runbooks

What you bring to Uplight:

• 2 to 5 years of software engineering experience using at least one of the major cloud providers, ideally in infrastructure or data platform roles
• Experience with Terraform or similar Infrastructure-as-Code tools for managing cloud resources
• Experience with Databricks or a similar data platform
• Proficiency in Python; working knowledge of SQL
• Some familiarity with data engineering concepts like ETL pipelines, data modeling, or workflow orchestration
• Familiarity with, or genuine openness to, working with AI coding agents and assistants; you don't need to be an expert, but you should be curious about using agentic AI thoughtfully and responsibly
• Comfortable asking questions, working through unclear requirements, and learning from the engineers around you

Bonus points:

• Familiarity with Databricks account-level administration & Unity Catalog
• Experience with multi-cloud (AWS, GCP)
• Knowledge of data governance, access control, and compliance practices
• Additional data engineering experience with Spark, Delta Lake, or similar frameworks
• Experience tuning big data workloads for performance and cost efficiency
• Contributed to machine learning productization and/or have used MLOps frameworks