Data Engineer

Autosavvy
Woods Cross, UT, United States
13 days ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Experienced
Experience required
3 years minimum
Working hours
Regular working hours
Job source

Tech stack

Microsoft Excel Artificial Intelligence Airflow Microsoft Azure Cloud Storage Databases Continuous Integration Data Validation Information Engineering Extract Transform Load (ETL) Data Transformation Data Security
+31 more
Data Systems Database Queries Multi-Factor Authentication Ethernet Github Python (Programming Language) Machine Learning Microsoft SQL Server SQL Azure Operational Data Store Performance Tuning Power BI Software Engineering SQL Databases Systems Integration Wi-Fi Technology Data Logging Data Processing Freeform SQL Azure Data Factory Backend Git Data Lakes Integration Tests Build Tools Restful APIs GPT Data Pipelines Serverless Computing Custom Reports Web Api

Job description

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, * Take ownership of existing Azure-based pipelines and improve reliability
  • Deliver new data workflows with minimal oversight
  • Reduce manual or repetitive processes through automation
  • Improve performance and usability of reporting datasets

Within 6-12 months, you will:

  • Own a set of data pipelines or domains end-to-end
  • Establish and improve standards for data quality, testing, and pipeline reliability
  • Deliver measurable improvements in performance, maintainability, and operational efficiency
  • Contribute to shaping best practices for how data systems are built and scaled

What This Role is Not

  • Not a narrowly scoped or ticket-driven position
  • Not focused on building machine learning or AI model

Team & Growth

  • You will work directly with the senior technical lead focused on system design and strategy
  • You will have meaningful input into how solutions are implemented and improved
  • Opportunity to grow into ownership of larger systems and architecture
  • As systems scale, this role can expand into broader engineering or platform ownership
  • Opportunity to mentor future hires and influence engineering and hiring standards as the team grows

Why This Role

  • Be the first dedicated data engineering hire and help shape how data systems are built and scaled
  • High-trust, low-bureaucracy environment with real ownership and decision-making autonomy
  • Build systems that directly impact business operations, pricing, and reporting
  • Focus on meaningful engineering work rather than one-off tasks

Requirements

  • 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 preferred)
  • Experience optimizing data workflows for cost and performance in Azure
  • Experience supporting Power BI through well-structured datasets and optimized data models
  • Proficiency with Excel for data analysis, validation, and ad hoc reporting
  • Experience with observability and monitoring (e.g., logging, metrics, alerting in Azure)

Mindset & Approach

  • Curious and proactive in learning new tools, technologies, and industry practices
  • Stays current with modern data engineering and software development patterns
  • Comfortable leveraging AI-assisted development tools (e.g., Claude, Codex, ChatGPT, Grok, etc.) to improve productivity and solution quality
  • Able to critically evaluate AI-generated output and apply sound engineering judgment
  • Continuously looks for ways to improve systems, processes, and developer efficiency
  • Bias toward simple, pragmatic solutions over unnecessary complexity

Ownership & Working Style

  • Comfortable working independently with minimal oversight while aligning to defined priorities and architecture
  • Takes ownership of problems from initial concept through implementation and iteration
  • Proactively identifies gaps, inefficiencies, and opportunities for improvement
  • Communicates clearly on progress, tradeoffs, and blockers without needing constant direction
  • Comfortable asking for clarification when needed to ensure alignment and avoid misdirection, * Ability 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., * Valid driver’s license with acceptable driving record
  • Ability to pass a background check
  • Authorized to work in the United States
  • Requirement of Multi-Factor Authentication apps on cell phone

Benefits & conditions

Pulled from the full job description

  • Pet insurance
  • Health insurance
  • Paid time off
  • Employee discount
  • Vision insurance
  • Health savings account
  • Dental insurance, * Comprehensive Benefits: Medical, Dental, and Vision coverage, HSA match, TelaDoc, Pharmacy Discount Programs, and Employer paid Life Insurance
  • Employee Assistance Program: Free of charge for personal uses such as support and general resources
  • Additional Perks: Pet Insurance, Gym Discounts, and an Employee Vehicle Purchase Program, Volunteer PTO Program
  • Retirement Savings: Employer matching contributions
  • Paid Time Off: Among the best PTO policies in the industry
  • Paid Holidays: 7 Major Holidays

About the company

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., All offers of employment at AutoSavvy are contingent upon clear results of a thorough background check and motor vehicle report (MVR). Background checks and MVRs will be conducted on all final candidates offered employment. AutoSavvy participates in E-Verify and will provide the federal government with your Form I-9 information to confirm that you are authorized to work in the United States.

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