Data Engineer building and optimising the Azure - based data platform at Castle Trust Bank. Collaborating to deliver scalable, reliable solutions empowering decision - making across the Bank.
About the role
- Software Engineer on the Data Platform team at Mia Labs. Focusing on backend Python engineering and building AI-enabled data workflows while modernizing dealership 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.
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.
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.
Job title
Job type
Experience level
Salary
Not specified
Degree requirement
Tech skills
Location requirements
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