Software Engineer (Data Platform)

Mia Labs, Inc.•Austin, TX

1d•Hybrid

About The Position

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. About Mia 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. About the Role: We are seeking a highly skilled and experienced 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.

Requirements

4+ 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 (BigQuery, 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 with minimal friction
Strong communication and ownership; comfortable working directly with senior cross-functional stakeholders
Experience with API integrations.
Demonstrated ability to mentor and inspire team members.
Excellent problem-solving and communication skills.

Nice To Haves

Experience with BI or analytics platforms such as Hex, Metabase, or Looker
Experience with managed ELT ingestion tools such as Fivetran or Stitch
Experience with identity resolution, entity linking, or customer 360/CDP systems
Experience building customer-facing analytics or reporting products
Familiarity with automotive data domains (dealerships, DMS/CRM, service operations)

Responsibilities

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.

Benefits

Equity participation through stock options.
Fully paid health, vision & dental insurance for employees.
Flexible PTO and hybrid schedule (3 days / week in downtown Austin).
Free lunches, parking stipend provided, team events, and a casual, but get things done culture.

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