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Data Engineer Jobs in Layton, UT (NOW HIRING)

Data Engineer

Woods Cross, UT · On-site

$108K - $129K/yr

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 ...

Data Engineer

Salt Lake City, UT · On-site

$110K - $133K/yr

Make an Impact We are looking for a Data Engineer who is proficient and experienced across the full dataflow lifecycle from requirements gathering through pipeline development and semantic layer ...

In data engineering at PwC, you will focus on designing and building data infrastructure and systems to enable efficient data processing and analysis. You will be responsible for developing and ...

In data engineering at PwC, you will focus on designing and building data infrastructure and systems to enable efficient data processing and analysis. You will be responsible for developing and ...

Data Engineers

Salt Lake City, UT · On-site +1

$110K - $133K/yr

As a Data Engineer, your responsibilities will include: 1. Design, develop, and maintain database architecture following industry best practices Design and implement scalable, secure, and high ...

In data engineering at PwC, you will focus on designing and building data infrastructure and systems to enable efficient data processing and analysis. You will be responsible for developing and ...

Data Engineers

Salt Lake City, UT · On-site

$99K - $124K/yr

As a Data Engineer, your responsibilities will include: 1. Design, develop, and maintain database architecture following industry best practices Design and implement scalable, secure, and high ...

Industry/Sector Not Applicable Specialism Data, Analytics & AI Management Level Manager & Summary The Opportunity As a Data Engineer - Manager, you will play a pivotal role in transforming raw data ...

Industry/Sector Not Applicable Specialism Data, Analytics & AI Management Level Senior Associate & Summary The Opportunity As a Data Engineer - Senior Associate, you will focus on designing and ...

Senior Big Data Engineer

Salt Lake City, UT · On-site

$54 - $71.25/hr

Responsibilities • Participate in the engineering and administration of big data systems. • Apache Storm/Java development for both data transformation and augmentation. • Employ best practices ...

Data Strategy-Manager

Salt Lake City, UT · On-site

$99K - $232K/yr

... Data Engineer / Azure Solutions Architect - Google Professional Data Engineer - DAMA CDMP (Certified Data Management Professional) - Informatica Certified Professional - Alation Certified Data ...

Data Analytics Engineer

Ogden, UT

$112K - $134K/yr

Data Analyst Engineer to design, develop, and maintain scalable data solutions that support the bank's Business Intelligence pipelines, modeling, and reporting. This role bridges data engineering ...

... Data Engineer / Azure Solutions Architect - Google Professional Data Engineer - DAMA CDMP (Certified Data Management Professional) - Informatica Certified Professional - Alation Certified Data ...

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Showing results 1-20

Data Engineer information

See Layton, UT salary details

$40.4K

$117.9K

$161.3K

How much do data engineer jobs pay per year?

As of Jun 14, 2026, the average yearly pay for data engineer in Layton, UT is $117,856.00, according to ZipRecruiter salary data. Most workers in this role earn between $104,000.00 and $124,900.00 per year, depending on experience, location, and employer.

What is the difference between Data Engineer vs Data Scientist?

AspectData EngineerData Scientist
Primary FocusBuilding and maintaining data pipelines and infrastructureAnalyzing data to extract insights and create models
SkillsSQL, ETL, programming (Python, Java), database managementStatistics, machine learning, data analysis, programming (Python, R)
Work EnvironmentData warehouses, cloud platforms, backend systemsData analysis environments, research labs, visualization tools
Common ToolsApache Spark, Hadoop, Airflow, SQLJupyter, RStudio, Tableau, scikit-learn

Data Engineers focus on creating and maintaining the infrastructure that allows data to be collected, stored, and processed efficiently. Data Scientists analyze this data to generate insights, build predictive models, and support decision-making. While their skills overlap, Data Engineers are more involved in data pipeline development, whereas Data Scientists focus on data analysis and modeling.

What are the key skills and qualifications needed to thrive as a Data Engineer, and why are they important?

To thrive as a Data Engineer, you need a strong background in computer science, data modeling, and programming languages such as Python or Java, often coupled with a relevant degree. Familiarity with ETL tools, big data frameworks (like Hadoop or Spark), and cloud platforms (such as AWS or Azure) is typically required, along with certifications like AWS Certified Data Analytics. Strong problem-solving skills, attention to detail, and effective communication set exceptional data engineers apart. These skills and qualities are essential for building robust data pipelines, ensuring data quality, and supporting data-driven decision-making across organizations.

Are data engineers highly paid?

Data engineers are generally well-paid due to their specialized skills in designing and maintaining data infrastructure, with salaries often higher than many other IT roles. Compensation varies based on experience, location, and industry, but strong technical skills in programming, databases, and cloud platforms typically lead to higher earnings.

What Does a Data Engineer Do?

The job duties of a data engineer involve helping with the development of systems, software, and infrastructure used to process, store and analyze data. Your responsibilities in this career include working to install data management software. Your employer may expect you to perform maintenance and install updates to all software and systems that they use for data acquisition, management, and analysis. Data engineers also analyze existing data systems to find ways to improve efficiency and accessibility. You then suggest upgrades or changes based on your assessment.

What are Data Engineers?

Data Engineers are IT professionals who design, construct, install, and maintain large-scale processing systems and other infrastructure for collecting, storing, and analyzing data. They build and optimize data pipelines and architectures that allow organizations to efficiently access and use data for business insights. Data Engineers work closely with data scientists, analysts, and other stakeholders to ensure that data is reliable, accessible, and secure. Their responsibilities often include working with databases, cloud platforms, and big data tools.

How do Data Engineers typically collaborate with Data Scientists and Analysts within an organization?

Data Engineers play a crucial role in ensuring that Data Scientists and Analysts have reliable, well-structured data for their projects. This collaboration often involves building and maintaining data pipelines, optimizing data storage solutions, and troubleshooting data quality issues. Regular communication and agile teamwork are common, with Data Engineers frequently participating in meetings to understand analytical requirements and adjust data processes accordingly. By working closely together, these teams can quickly iterate on data models and deliver actionable insights to drive business decisions.

What does a data engineer actually do?

A data engineer designs, builds, and maintains the infrastructure and pipelines that enable organizations to collect, store, and process large volumes of data. They work with tools like SQL, Python, and cloud platforms to ensure data is accessible, reliable, and ready for analysis by data scientists and analysts.

Is a data engineer entry level?

Data engineering is typically an intermediate to senior role that requires experience with programming, databases, and data pipeline tools. Entry-level data engineering positions may be available for candidates with relevant internships or strong foundational skills in SQL, Python, or cloud platforms, but most roles expect some prior experience. Certifications or coursework in data management can also be beneficial for those starting out.

What engineer makes $500,000 a year?

Senior data engineers with extensive experience, advanced skills in big data tools, and leadership roles can earn salaries approaching or exceeding $500,000 annually, especially in high-cost-of-living areas or large tech companies. Such compensation often includes base salary, bonuses, and stock options. Achieving this level typically requires years of expertise and a strong track record in data architecture and engineering.
What are the most commonly searched types of Data Engineer jobs in Layton, UT? The most popular types of Data Engineer jobs in Layton, UT are:
What job categories do people searching Data Engineer jobs in Layton, UT look for? The top searched job categories for Data Engineer jobs in Layton, UT are:
What cities near Layton, UT are hiring for Data Engineer jobs? Cities near Layton, UT with the most Data Engineer job openings:
Infographic showing various Data Engineer job openings in Layton, UT as of June 2026, with employment types broken down into 6% Internship, 82% Full Time, 6% Part Time, and 6% Contract. Highlights an 94% In-person, and 6% Remote job distribution, with an average salary of $117,856 per year, or $56.7 per hour.

Data Engineer

AutoSavvy

Woods Cross, UT • On-site

$108K - $129K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 27 days ago


Job description

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 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

What Success Looks Like

Within the first 90 days, you will:

  • 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

Physical Requirements

  • Ability to sit at a desk for extended periods, perform repetitive tasks like typing, and frequentuse 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 Environment

  • In office meetings out of theWoods Cross, UT location.

Requirements
  • 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:

  • 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: 7Major Holidays

AutoSavvy provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state, or local laws.

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.