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Data Engineer Jobs in Layton, UT (NOW HIRING)

TAB Bank

Data Analytics Engineer

Ogden, UT · On-site

$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 ...

Pwc

Data Strategy-Senior Manager

Salt Lake City, UT · On-site

$124K - $280K/yr

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

Armaninollp

Senior ERP Data Engineer

Salt Lake City, UT

$102K - $139K/yr

Data engineering, ETL/ELT development, or enterprise data integration * Operating production data pipelines endtoend, including monitoring, testing, and support * Strong experience applying SDLC best ...

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All JobsData Engineer JobsData Engineer Jobs in Layton, UT

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.
More about Data Engineer jobs
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:
Data Engineer jobs near you
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 Analytics Engineer

Data Analytics Engineer

TAB Bank

Ogden, UT • On-site

$112K - $134K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 12 days ago

Job description

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, analytics, and business intelligence by transforming complex data into reliable, actionable intelligence and insights for strategic decision-making across the organization. The ideal candidate combines strong analytical skills with technical expertise in SQL, data modeling, Python pipelines, and visualization tools.
Essential Duties and Responsibilities:
  • Collect, clean, and analyze large datasets from multiple sources
  • Design and maintain data models, dashboards, and reporting systems
  • Develop and optimize SQL queries, ETL processes, and data pipelines
  • Collaborate with business stakeholders to understand reporting and analytics needs
  • Monitor data quality, integrity, and consistency across systems
  • Build automated reports and visualizations using BI tools
  • Identify trends, patterns, and opportunities through statistical analysis
  • Support decision-making with data-driven recommendations
  • Work with data engineers and software teams to improve data architecture
  • Document data definitions, workflows, and technical processes

Required education and experience:
Bachelor's degree in Computer Science, Information Systems, Data Analytics, Statistics, or related field
  • 3+ years of experience in business intelligence, analytics engineering, or data engineering
  • Advanced SQL skills and experience working with large relational and cloud-based datasets
  • Proficiency in Python or another analytics/programming language
  • Understanding of data warehousing and data modeling concepts, including dimensional and normalized models
  • Experience with BI and visualization tools such as Power BI or Tableau
  • Strong analytical, communication, and problem-solving skills
  • Or an equivalent combination of education and experience that provides the required knowledge, skills, and abilities

Preferred education and experience:
MSSQL and Python experience preferred
  • Experience with large scale streaming pipelines is a plus
  • Snowflake experience is a plus
  • Financial Services and Commercial Banking experience is a plus

Competencies:
Proficient in Python and SQL
  • Data warehousing and modeling, including dimensional and normalized models
  • Tableau or Power BI
  • Must have independent problem-solving skills and ability to develop solutions to complex analytical/data modeling problems
  • Excellent verbal and written communication skills and the ability to interact professionally with a diverse group including executives, managers, and subject matter experts
  • Successfully engage in multiple initiatives simultaneously
  • Work successfully in a team environment using Agile Scrum methodologies
  • Willing to suggest improvements along with offering possible solutions

TAB Bank Offers:
  • Onsite Gym
  • Tuition Reimbursement
  • Paid Holidays
  • Gym Reimbursement
  • College Scholarships for Employees and Families
  • 401(k)
  • Paid Time Off (PTO)
  • Employee Assistance Program (EAP)
  • I Made the Grade
  • Holiday Club Program
  • Medical, Dental, Vision, Life and AD&D, Voluntary Disability, Flex Spending & Dependent Care

TAB Bank will not sponsor applicants for work visas.
Equal Opportunity Employer
This employer is required to notify all applicants of their rights pursuant to federal employment laws.
For further information, please review the Know Your Rights notice from the Department of Labor.

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