Data Engineer

**Data Engineer** (Mid-Level) Utah (Local Required) ### **Overview** AutoSavvy is a fast-growing automotive retailer focused on providing high-quality, branded title vehicles at competitive prices nationwide. We leverage data and internal systems to drive operational efficiency, pricing strategy, and decision-making across the business. We are looking for a Data Engineer to help scale our internal data and automation capabilities within a Microsoft Azure environment. This role focuses on building and maintaining data pipelines, improving reporting datasets, and developing internal tools that support operational pricing, and reporting decisions. You will be the first dedicated data engineering hire, helping define how data systems are built, maintained, and scaled across the organization, working directly with the technical lead responsible for architecture and strategy. This role is focused on execution, ownership, and building systems that scale. Our stack primarily includes Azure SQL, Python-based data workflows, Azure Functions and Container Apps for scheduled and event-driven workflows, and Azure Blob Storage. **Scope of the Role** You will work across data pipelines, reporting datasets, and backend workflows. This role requires someone comfortable operating across multiple areas and building practical, scalable solutions. **What You'll Work On (Examples)** Optimize and extend existing pipelines improving reliability and reducing job runtimes while designing new pipelines and databases as needed - Build and maintain pipelines that ingest, transform, and standardize operational data - Improve performance and reliability of SQL-based datasets - Automate internal workflows that require manual data handling - Design clean, reusable data models to support business metrics and dashboards - Integrate external APIs and internal systems into centralized data workflows **Responsibilities** **Data Pipelines & Azure Infrastructure** - Build, maintain, and optimize ETL/ELT pipelines using Azure services - Work with data across Azure SQL, Blob Storage, and related services - Ensure data quality, reliability, and performance through monitoring and troubleshooting - Implement data validation and testing (e.g., data quality checks, unit/integration tests) to ensure correctness and maintainability **Data Modeling & Reporting Support** - Develop and maintain clean, reliable datasets for reporting and analytics - Collaborate on data models that support business metrics and dashboards - Write and optimize complex SQL queries for performance and clarity **Automation & Internal Tooling** - Build Python-based scripts and services to automate internal workflows - Integrate with external APIs and internal systems - Reduce manual processes through automation **Collaboration & Execution** - Execute against defined architecture and technical direction - Contribute to solution design - Communicate progress, blockers, and improvements clearly **Required Qualifications** - 3-5 years of experience in data engineering or similar role - Ability to work independently on well-scoped problems with minimal guidance - Strong SQL skills (advanced querying, performance tuning, data transformations) - Proficiency in Python for data processing and automation - Experience writing maintainable, testable Python code - Experience using Git for version control (e.g., GitHub), including branching and pull request workflows - Hands-on experience with Azure data services, including: - Azure SQL Database or SQL Server - Experience orchestrating data workflows (e.g., Azure Functions, Container Apps, Airflow, or similar) - Azure Blob Storage or Data Lake - Experience building and maintaining ETL/ELT pipelines - Experience working with large, structured datasets **Preferred Qualifications** - Familiarity with data modeling for analytics and reporting - Experience integrating with REST APIs and external data sources - Understanding of CI/CD practices and tooling (Azure DevOps p…