Data Engineer

Data EngineerAutoSavvy 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 RoleYou 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)Build and maintain pipelines that ingest, transform, and standardize operational dataImprove performance and reliability of SQL-based datasetsAutomate internal workflows that require manual data handlingDesign clean, reusable data models to support business metrics and dashboardsIntegrate external APIs and internal systems into centralized data workflowsResponsibilitiesBuild, maintain, and optimize ETL/ELT pipelines using Azure servicesWork with data across Azure SQL, Blob Storage, and related servicesEnsure data quality, reliability, and performance through monitoring and troubleshootingImplement data validation and testing (e.g., data quality checks, unit/integration tests) to ensure correctness and maintainabilityDevelop and maintain clean, reliable datasets for reporting and analyticsCollaborate on data models that support business metrics and dashboardsWrite and optimize complex SQL queries for performance and clarityBuild Python-based scripts and services to automate internal workflowsIntegrate with external APIs and internal systemsReduce manual processes through automationExecute against defined architecture and technical directionContribute to solution designCommunicate progress, blockers, and improvements clearlyRequired Qualifications3-5 years of experience in data engineering or similar roleAbility to work independently on well-scoped problems with minimal guidanceStrong SQL skills (advanced querying, performance tuning, data transformations)Proficiency in Python for data processing and automationExperience writing maintainable, testable Python codeExperience using Git for version control (e.g., GitHub), including branching and pull request workflowsHands-on experience with Azure data services, including:Azure SQL Database or SQL ServerExperience orchestrating data workflows (e.g., Azure Functions, Container Apps, Airflow, or similar)Azure Blob Storage or Data LakeExperience building and maintaining ETL/ELT pipelinesExperience working with large, structured datasetsPreferred QualificationsFamiliarity with data modeling for analytics and reportingExperience integrating with REST APIs and external data sourcesUnderstanding of CI/CD practices and tooling (Azure DevOps preferred)Experience optimizing data workflows for cost and performance in AzureExperience supporting Power BI through well-structured datasets and optimized data modelsProficiency with Excel for data analysis, validation, and ad hoc reportingExperience with observability and monitoring (e.g., logging, metrics, alerting in Azure)Mindset & ApproachCurious and proactive in learning new tools, technologies, and industry practicesStays current with modern data engineering and software development patternsComfortable leveraging AI-assisted development tools (e.g., Claude, Codex, ChatGPT, Grok, etc.) to improve productivity and solution qualityAble to critically evaluate AI-generated output and apply sound engineering judgmentContinuously looks for ways to improve systems, processes, and developer efficiencyBias toward simple, pragmatic solutions over unnecessary complexityOwnership & Working StyleComfortable working independently with minimal oversight while aligning to defined priorities and architectureTakes ownership of problems from initial concept through implementation and iterationProactively identifies gaps, inefficiencies, and opportunities for improvementCommunicates clearly on progress, tradeoffs, and blockers without needing constant directionComfortable asking for clarification when needed to ensure alignment and avoid misdirectionWhat Success Looks LikeWithin the first 90 days, you will:Take ownership of existing Azure-based pipelines and improve reliabilityDeliver new data workflows with minimal oversightReduce manual or repetitive processes through automationImprove performance and usability of reporting datasetsWithin 6-12 months, you will:Own a set of data pipelines or domains end-to-endEstablish and improve standards for data quality, testing, and pipeline reliabilityDeliver measurable improvements in performance, maintainability, and operational efficiencyContribute to shaping best practices for how data systems are built and scaledWhat This Role is NotNot a narrowly scoped or ticket-driven positionNot focused on building machine learning or AI modelTeam & GrowthYou will work directly with the senior technical lead focused on system design and strategyYou will have meaningful input into how solutions are implemented and improvedOpportunity to grow into ownership of larger systems and architectureAs systems scale, this role can expand into broader engineering or platform ownershipOpportunity to mentor future hires and influence engineering and hiring standards as the team growsWhy This RoleBe the first dedicated data engineering hire and help shape how data systems are built and scaledHigh-trust, low-bureaucracy environment with real ownership and decision-making autonomyBuild systems that directly impact business operations, pricing, and reportingFocus on meaningful engineering work rather than one-off tasksPhysical RequirementsAbility to sit at a desk for extended periods, perform repetitive tasks like typing, and frequent use a video calls.Dedicated Workspace: A quiet, private area free from noise and distractions to ensure productivity and data security.High-Speed Internet: Reliable broadband internet, often requiring a wired Ethernet connection to the router rather than Wi-Fi for stability.Work EnvironmentIn office meetings out of the Woods Cross, UT location.RequirementsValid driver's license with acceptable driving recordAbility to pass a background checkAuthorized to work in the United StatesRequirement of Multi-Factor Authentication apps on cell phoneBenefits:Comprehensive Benefits : Medical, Dental, and Vision coverage, HSA match, TelaDoc, Pharmacy Discount Programs, and Employer paid Life InsuranceEmployee Assistance Program : Free of charge for personal uses such as support and general resourcesAdditional Perks : Pet Insurance, Gym Discounts, and an Employee Vehicle Purchase Program, Volunteer PTO Program