4+ years of software engineering experience with strong Python fundamentals
Hands-on experience with modern data stack tools like Dagster, dbt, and cloud data warehouses (BigQuery, Snowflake)
Strong SQL and data modeling exposure, including dimensional modeling and data quality testing
Experience operating in cloud environments (Azure, GCP, or AWS) with CI/CD and observability practices
Practical experience in integrating AI/LLM tooling into workflows
Ability to transition between data engineering and general backend engineering seamlessly
Strong communication skills and ability to engage with senior stakeholders
Responsibilities
Design and maintain scalable backend systems using Python for data services
Ship data orchestration assets using modern workflow tools
Develop and optimize data models for various layers
Improve data quality and reliability for analytics
Deliver reusable reporting foundations with tested metrics
Build AI-enabled data workflows and extraction pipelines
Collaborate with product, finance, sales, and leadership for data products
Contribute to backend engineering when needed
Benefits
Equity participation through stock options
Fully covered health, vision, and dental insurance for employees
Flexible PTO and hybrid work schedule
Free lunches and parking stipend, along with team events
Casual culture focused on productivity
Full Job Description
About the Role:
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.
What You Will Do::
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.
What We Want You to Have:
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 (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.
What Makes You Stand Out (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)
Why Mia
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.
Compensation
Compensation for this position will be competitive with current market rates and reflective of the candidate's experience, skills and qualifications.
