1

From Home Data Platform Engineer Jobs in Utah (NOW HIRING)

Senior Data Engineer

Lehi, UT · On-site

$99K - $135K/yr

Experience migrating workloads from Snowflake, Azure, SQL Server, Teradata, or other platforms to ... Cloud Data Engineering (GCP / BigQuery) - Advanced * ELT Pipeline Development - Advanced * Data ...

Data & Infrastructure Engineer

Draper, UT · On-site

$107K - $128K/yr

... platform that powers WorkBay's operations, analytics, and strategic decision-making. You will ... Maintain and extend scheduled data sync pipelines that pull from third-party APIs into our ...

Staff Data Architect

Lehi, UT · On-site

$59.75 - $77/hr

... from the ground up. We're building a new platform alongside our current one, so this role requires ... Guide and mentor data engineers through design reviews, technical documentation, and hands on ...

New

Senior Data Engineer

American Fork, UT

$94K - $128K/yr

... move data reliably from diverse source systems into a clean, well-governed data platform ... Define and drive data engineering standards that improve quality, reliability, and productivity ...

Sr. Product Manager, Core Data Platform

Draper, UT · Hybrid

$118K - $156K/yr

Partner closely with principal architects and engineering leads to make principled data modeling tradeoffs and communicate the implications broadly. * Ensure the data platform is easy to build ...

Distinguished Architect, Data Technology

Draper, UT · Hybrid

$59.50 - $76.75/hr

... platform is positioned for future innovation and growth. * Collaborate with Product and Engineering leadership to define and communicate the product vision and strategy from a data architecture ...

Senior Data Engineer

American Fork, UT · On-site

$94K - $128K/yr

... from our physical units in the field to a powerful Agentic AI platform--that allows our customers ... ABOUT THIS ROLE As Senior Data Engineer, you will own and evolve LVT's core data platform ...

Showing results 41-60

From Home Data Platform Engineer information

What is a from home data platform engineer?

From Home Data Platform Engineers are professionals who design, build, and maintain the infrastructure and tools that allow organizations to collect, store, process, and analyze large volumes of data, all while working remotely. They work with cloud platforms, databases, and data pipelines to ensure data is accessible, reliable, and secure for business needs. Their role often involves collaborating with data scientists, analysts, and other engineers to support data-driven decision-making and optimize data workflows from a home office or remote location.

What are the key skills and qualifications needed to thrive as a from home data platform engineer?

To thrive as a From Home Data Platform Engineer, you need a strong background in computer science, data architecture, and cloud platforms, often supported by a relevant degree and experience with large-scale data systems. Proficiency with technologies like SQL, Python, Spark, Hadoop, and cloud services such as AWS, Azure, or GCP, along with certifications like AWS Certified Data Analytics or Google Professional Data Engineer, is typically required. Strong problem-solving abilities, self-motivation, and effective remote communication skills help you excel in a distributed work environment. These skills ensure reliable, scalable data infrastructure and seamless collaboration, which are critical to supporting business analytics and decision-making remotely.

What are some common challenges faced by a from home data platform engineer, and how can they be addressed?

As a From Home Data Platform Engineer, you may encounter challenges such as managing complex data pipelines remotely, ensuring data security, and maintaining effective communication with cross-functional teams. To address these, it’s important to utilize robust version control systems, follow best practices for data governance, and leverage collaboration tools like Slack or Jira for regular updates and troubleshooting. Additionally, setting up secure remote access and automated monitoring can help maintain the integrity and performance of data platforms while working from home.

What is the difference between From Home Data Platform Engineer vs From Home Data Analyst?

AspectFrom Home Data Platform EngineerFrom Home Data Analyst
Primary RoleDesigning, building, and maintaining data infrastructure and platformsAnalyzing data to generate insights and reports
Skills & CertificationsData engineering, SQL, cloud platforms, programming (Python, Java)Data analysis, SQL, visualization tools, statistical knowledge
Work EnvironmentCollaborates with data engineers, software developers, often in cloud environmentsWorks with business teams, data visualization tools, and reporting platforms
Industry UsageTech, finance, healthcare, where data infrastructure is criticalMarketing, sales, finance, and other sectors focusing on data insights

In summary, From Home Data Platform Engineers focus on building and maintaining the data infrastructure, while From Home Data Analysts interpret data to support business decisions. Both roles require strong SQL skills but differ in technical depth and focus areas.

What are the most commonly searched types of Data Platform Engineer jobs in Utah?

The most popular types of Data Platform Engineer jobs in Utah are:

What cities in Utah are hiring for From Home Data Platform Engineer jobs?

Cities in Utah with the most From Home Data Platform Engineer job openings:

Senior Data Engineer

Crew Career Center

Lehi, UT • On-site

$99K - $135K/yr

Full-time

Medical, Retirement, PTO

Posted 5 days ago


Job description

ABOUT THIS POSITION

Waystar is seeking a highly skilled Senior Data Engineer to join our Business Data & Architecture team and help advance our enterprise Data Modernization Program on Google Cloud Platform (GCP).
This is a senior individual contributor role focused on designing, building, and optimizing scalable data solutions that enable analytics, reporting, governance, and AI initiatives across the enterprise. The ideal candidate is a hands-on engineer with deep technical expertise in cloud data platforms, data modeling, ELT development, and modern engineering practices.
You will work across the full data lifecycle, from data ingestion and transformation to orchestration, quality, observability, and governance, helping deliver trusted and scalable data products that support business decision-making.

WHAT YOU'LL DO

Data Pipeline Development & Optimization

  • Design, build, and maintain scalable ELT pipelines into BigQuery using Fivetran, APIs, Python, and cloud-native services
  • Develop and optimize bronze, silver, and gold data layers following Medallion Architecture principles
  • Create and maintain reusable dbt models that support enterprise reporting, analytics, and self-service use cases
  • Design and implement scalable ingestion patterns for structured and semi-structured data
  • Troubleshoot and resolve complex data pipeline, transformation, and performance issues
  • Improve pipeline reliability, performance, scalability, and maintainability

Data Modeling & Analytics Enablement

  • Design and implement scalable data models supporting business intelligence, analytics, and operational reporting
  • Partner with business analysts, product owners, and stakeholders to understand and translate requirements into technical solutions
  • Develop reusable business-focused datasets and metrics aligned with enterprise standards
  • Support semantic modeling and reporting initiatives across business domains
  • Contribute to the standardization of enterprise metrics and reporting assets

Data Quality, Observability & Reliability

  • Implement automated data validation, testing, and data quality checks
  • Develop monitoring, alerting, and observability capabilities across the data platform
  • Investigate and resolve data anomalies, processing issues, and performance bottlenecks
  • Support operational excellence through logging, incident analysis, and root cause investigations
  • Ensure data consistency, accuracy, and reliability across ingestion and transformation processes

Platform Engineering & Automation

  • Develop and maintain orchestration workflows using Cloud Composer (Managed Airflow)
  • Contribute to CI/CD pipelines using GitHub and modern deployment practices
  • Support Infrastructure-as-Code initiatives using Terraform and platform automation tools
  • Improve engineering efficiency through automation, reusable components, and standard development patterns
  • Participate in platform optimization and modernization initiatives

Data Governance & Security

  • Support data classification, lineage, metadata management, and governance initiatives
  • Implement secure access controls and data protection practices aligned with enterprise standards
  • Partner with Data Governance teams to improve data discoverability and trust
  • Ensure compliance with regulatory, privacy, and security requirements
  • Contribute to documentation and operational standards for enterprise data assets

Collaboration & Continuous Improvement

  • Collaborate with engineers, architects, analysts, and business stakeholders across multiple domains
  • Participate in technical design reviews and engineering discussions
  • Perform peer code reviews and support engineering quality standards
  • Contribute to documentation, knowledge sharing, and reusable engineering practices
  • Evaluate new technologies and recommend platform improvements where appropriate

WHAT YOU'LL NEED

  • Bachelor's degree in computer science, Information Systems, Data Engineering, or a related field
  • 5+ years of experience in Data Engineering or a related technical discipline
  • Strong hands-on experience with Google Cloud Platform (GCP)
  • Advanced expertise in BigQuery
  • Strong experience with dbt and modern ELT development practices
  • Advanced SQL development and query optimization skills
  • Strong Python programming experience
  • Experience building scalable data pipelines and transformation frameworks
  • Experience working with APIs and data integration patterns
  • Experience with workflow orchestration tools such as Airflow or Cloud Composer
  • Experience with GitHub, source control, and CI/CD development practices
  • Strong understanding of dimensional modeling and analytics engineering concepts
  • Strong troubleshooting, problem-solving, and analytical skills
  • Excellent communication and collaboration skills

Preferred Qualifications

  • Experience supporting enterprise-scale data modernization programs
  • Experience migrating workloads from Snowflake, Azure, SQL Server, Teradata, or other platforms to BigQuery
  • Experience with Terraform and Infrastructure-as-Code practices
  • Familiarity with Google Dataplex, Knowledge Catalog, or metadata management solutions
  • Experience with Cloud Run, Cloud Functions, or serverless technologies
  • Experience implementing data quality, testing, and observability frameworks
  • Experience supporting healthcare, payments, or regulated industry environments
  • Familiarity with Data Mesh and domain-driven data ownership concepts
  • Experience supporting AI, machine learning, or advanced analytics initiatives

Competencies Overview

  • Cloud Data Engineering (GCP / BigQuery) - Advanced
  • ELT Pipeline Development - Advanced
  • Data Modeling & Analytics Engineering - Advanced
  • SQL & Query Optimization - Advanced
  • Python Development - Advanced
  • Data Quality & Observability - Advanced
  • Data Governance & Security - Strong
  • Problem Solving & Troubleshooting - Advanced
  • Collaboration & Stakeholder Partnership - Strong
  • Delivery Execution & Accountability - Strong

Skills Overview

Core Technologies

  • Google Cloud Platform (GCP)
  • BigQuery
  • dbt / dbt Cloud
  • Fivetran
  • Python
  • SQL
  • GitHub
  • Cloud Composer (Managed Airflow)
  • Cloud Functions
  • REST APIs and Data Integration Frameworks
  • CI/CD Pipelines

Preferred Technologies

  • Terraform
  • Dataplex
  • Knowledge Catalog
  • Cloud Run
  • Snowflake
  • Azure Data Factory (ADF)
  • Data Quality & Observability Platforms
  • Metadata Management Solutions

ABOUT WAYSTAR

Through a smart platform and better experience, Waystar helps providers simplify healthcare payments and yield powerful results throughout the complete revenue cycle.

Waystar's healthcare payments platform combines innovative, cloud-based technology, robust data, and unparalleled client support to streamline workflows and improve financials so providers can focus on what matters most: their patients and communities. Waystar is trusted by 1M+ providers, 1K+ hospitals and health systems, and is connected to over 5K commercial and Medicaid/Medicare payers. We are deeply committed to living out our organizational values: honesty; kindness; passion; curiosity; fanatical focus; best work, always; making it happen; and joyful,optimistic & fun.

Waystar products have won multiple Best in KLAS or Category Leader awards since 2010 and earned multiple #1 rankings from Black Book surveys since 2012. The Waystar platform supports more than 500,000 providers, 1,000 health systems and hospitals, and 5,000 payers and health plans. For more information, visit waystar.comor follow @Waystaron Twitter.

WAYSTAR PERKS

  • Competitive total rewards (base salary + bonus, if applicable)
  • Customizable benefits package (3 medical plans with Health Saving Account company match)
  • We offer generous paid time off for our non-exempt team members, starting with 3 weeks +13 paid holidays, including 2 personal floating holidays. We also offer flexible time off for our exempt team members + 13 paid holidays
  • Paid parental leave (including maternity + paternity leave)
  • Education assistance opportunities and free LinkedIn Learning access
  • Free mental health and family planning programs, including adoption assistance and fertility support
  • 401(K) program with company match
  • Pet insurance
  • Employee resource groups

Waystar is proud to be an equal opportunity workplace. We celebrate, value, and support diversity and inclusion. Qualified applicants will receive consideration for employment without regard to race, color, religion, age, sex, national origin, disability status, genetics, marital status, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state, or local laws.

This applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation, and training.