Senior Software Engineer; Data Platform

The Opportunity

The $1.2T automotive industry is a pillar of American culture, representing nearly 5% of U.S. GDP and shaping how people live and move every day. At the center of this ecosystem are dealerships—trusted local businesses that help consumers navigate one of the most important purchases they make.

Today, the industry is at an inflection point. Consumers expect the same speed, personalization, and convenience they experience in modern digital-first industries. At the same time, tighter margins and rising costs are driving a need for operational efficiency beyond what traditional software can support. Together, these shifts create a powerful opportunity to reimagine how dealerships deliver seamless experiences and build lasting customer relationships.

Dealers who modernize how they communicate and operate will unlock efficiency, deepen loyalty, and win long-term relationships. It is time to upgrade automotive retail to the 21st century.

Mia Labs is an investor-backed startup on a mission to modernize dealership operations and transform the automotive consumer experience. Our AI agent, Mia, turns every call or inquiry into an opportunity, improving customer satisfaction and dealership performance through automation that feels human. We are trusted by some of the nation's largest dealership groups and are rapidly scaling our team, product offerings, and customer base.

We are seeking a highly skilled and experienced Senior Software Engineer on the Data Platform team to join our fast-paced startup. This role emphasizes backend Python engineering with genuine data platform depth and high comfort with AI-powered workflows. You will own meaningful parts of our data infrastructure while also contributing to core backend Python systems as priorities shift.

• Design, develop, and maintain scalable backend systems using Python for data services, pipelines, and scheduled jobs
• Design and ship data orchestration assets, jobs, and sensors using modern workflow tooling
• Develop and optimize data models across staging, dimensional, fact, and mart layers
• Improve data quality, observability, and reliability for downstream analytics and reporting
• Deliver dealer and group-level reporting foundations with reusable, well-tested metrics
• Build AI-enabled data workflows, including batch extraction pipelines, evaluation loops, and cost-aware LLM integration patterns
• Partner directly with product, finance, sales, and leadership to turn ambiguous asks into production-grade data products
• Contribute to broader backend engineering in Python/FastAPI when the business requires it

• Lead system design and architecture discussions, ensuring technical scalability and maintainability.
• Apply best practices in software development, including testing, CI/CD pipelines, and code quality.
• Mentor and guide team members, fostering technical growth and collaboration.
• Stay current with technology advancements relevant to our domain, including AI/ML, and evaluate their potential application.

• 5+ years of professional software engineering experience with strong Python fundamentals
• Hands-on experience with modern data stack tools such as Dagster, dbt, and a cloud data warehouse (Big Query, Snowflake, or similar)
• Strong SQL and data modeling exposure (dimensional modeling, incremental patterns, data quality testing)
• Experience operating in cloud environments (Azure, GCP, or AWS) with production-grade practices: CI/CD, observability, secrets management
• Practical experience integrating AI/LLM tooling into real workflows — LLM provider APIs, prompt iteration, eval-minded development, or batch processing at scale
• Ability to move between data engineering and general backend engineering…