Data Engineer

• Responsible for designing, developing, and maintaining data warehousing solutions to support the organization's data integration, analysis, and reporting needs
• Overseeing the maintenance and security measures of the company databases
• Designs and architects’ data warehouse solutions that meet scalability, reliability, and performance goals
• Develops and implements data models, schemas, and ETL processes to extract, transform, and load data from various sources into the data warehouse
• Implement data quality controls and validation processes to ensure data integrity and consistency
• Identify and resolve data-related issues, including data quality problems, data transformation errors, and performance bottlenecks
• Provides general direction, design, maintenance, and control of company databases
• Responsible for troubleshooting and solving problems relative to current environment and architecture using a wide range of techniques to detect, identify and eliminate database problems
• Develops, documents and enforces standards for access to the database
• Write SQL queries to support ad-hoc reporting and data analysis
• Develop documentation on report development processes and procedures
• Perform other duties as assigned.

Junior Data Warehouse Engineer

• Lead a team of 2-3 engineers
• Working with fellow Nava engineers to design, review, and build well-crafted software
• Working in an agile manner to efficiently ship new features that meet user needs
• Design and develop scalable data ingestion and processing pipelines
• Implement large-scale data ecosystems within cloud-based platforms that include data management and data governance of structured and unstructured data
• Implement data validation and quality checks to ensure accuracy and consistency
• Work with cross-functional project teams to gather business requirements and translate to detailed technical specifications
• Work with Government partners to assist and develop data engineering applications and pipelines that will enable data services and processing capabilities
• Participate in software design and code reviews
• Maintain security and privacy standards in all aspects of the data pipeline
• Taking part in hiring activities (e.g., submitting referrals, conducting interviews, and attending interview debriefs), as needed

Senior Software Engineer, Data

• Design and implement the canonical data model for Vultr’s control plane ERP transformation: product catalog, chart of accounts, financial transactions, cost centers
• Build and maintain the internal APIs and event streams that Finance, Analytics, and downstream systems consume
• Refactor existing administer code toward clean domain boundaries (no more conflated orders/ledger/report tables)
• Implement data upgrade/migration paths from legacy schemas without breaking production
• Write the integration layer between administer and Vultr's existing billing, provisioning, and reporting systems
• Establish data validation and integrity checks across the financial data layer
• Collaborate with the Product Manager to translate finance domain requirements into durable schema designs
• Document architectural decisions and data model contracts for downstream consumers

Senior Software Engineer, ERP, Data & Domain

• Own the building, maintenance, and optimization of pipelines to ingest data from both operational databases and third-party tools into a data lake/warehouse.
• Architect highly efficient ingestion patterns that handle evolving data schemas and high-volume, multi-source data streams seamlessly.
• Optimize pipeline performance to ensure maximum uptime, high throughput, and cost-effective compute usage.
• Use dbt to transform raw data within the data warehouse into structured, production-ready schemas.
• Write templated SQL and Jinja code to enforce macro-driven, modular, and DRY (Don't Repeat Yourself) development practices.
• Perform rigorous data quality checks by implementing native dbt tests.
• Set up monitoring and alerting frameworks around both ingestion routines and dbt builds.
• Track pipeline health metrics to measure and report on overall data freshness and platform reliability.
• Build data applications that interact with the data warehouse to empower decentralized self-service analytics.
• Build internal tooling and libraries to facilitate analytics and ML work.

Staff Data Engineer

• Own and extend the Python-based ETL job orchestration engine: add new job types, monitor execution, and resolve production failures
• Build and maintain data pipelines powering operational reporting for scheduling, finance, credentialing, and clinical operations
• Integrate data sources into the warehouse - EHR (NextGen), CRM (HubSpot), HR platforms (ADP, Lever), credentialing (Modio), call center (Five9), and other third-party APIs
• Optimize high-frequency SQL workloads
• Support and extend custom AI agents
• Maintain HIPAA compliance across all data handling: enforce access controls, audit logging, and PHI segregation in pipelines and reporting layers
• Write and maintain version-controlled code in the GitHub repository

• Design, develop, and maintain scalable ETL/ELT pipelines using Databricks and Python.
• Build, test, and support integrations between Databricks, Oracle, and downstream systems.
• Develop and maintain high-quality data extracts for internal and external stakeholders.
• Own and document inbound and outbound data feeds.
• Monitor data pipelines for performance, reliability, and quality; identify and resolve issues.
• Design and optimize data models supporting operational, analytical, and financial reporting.
• Contribute to continuous improvement of the data platform using industry best practices.
• Partner with technical and business stakeholders to gather requirements and deliver solutions.
• Support internal applications and ensure business continuity.
• Collaborate effectively across engineering and cross-functional teams.

• Designs and develops moderately complex queries, objects, ETL packages, reporting structures, and other objects necessary to support detailed analysis and self-service reporting needs.
• Collaborates with analytics and business teams to create and improve data models that feed BI tools, increasing data accessibility, and fostering data-driven decision making across the organization.
• Takes ownership of the health, reliability, and security of the data platform by designing and implementing processes and solutions that proactively monitor data delivery across the full pipeline — ensuring data is accurate, complete, consistent, and timely from source ingestion through gold layer curation.
• Investigates, diagnoses, and resolves complex data pipeline failures across all system layers; uses findings to drive pipeline improvements and communicates status, root cause, and resolution clearly to the team throughout the full lifecycle of an incident.
• Assists with the development and delivery of data solutions, including data pipelines, API integration, and other structures and processes to support the data platform
• Identifies, designs, and implements internal process improvements, including the automation of manual processes, optimization of data delivery, and refactoring of code for improved performance
• Builds pipelines to enable the optimal extraction, transformation, and loading of data from a wide variety of data sources
• Provides strategic assistance to BI leadership and the BI team by making recommendations in the areas of data management and best practices
• Collaborates with developers, database administrators, data architects, and others on reporting and data management projects as needed
• Takes on other duties needed to help drive our Purpose, fulfill our Brand Principles, and abide by our Organization’s Values

Data Engineer II

• Provide leadership in developing data marts, designing data models, implementing ETL processes, and ensuring data usability for clients.
• Lead the physical design and implementation of databases for complex projects, optimizing data presentation for reporting tools.
• Develop and maintain standards for data warehouse elements, such as architectures, models, tools, and databases ensuring it aligns with best practices.
• Provide troubleshooting support for data warehouses and address technical issues promptly.
• Design, implement, and operate data warehouse systems to balance optimization of data access and resource utilization to meet performance requirements.
• Perform complex system and data analysis, using SQL, PLSQL, Python, and other languages to develop solutions through advanced programming and analysis.
• Build robust processes to streamline data flow by developing data warehouse process models, including sourcing, loading, transformation, and extraction, to support data integration pipelines.
• Create and manage supporting documentation, including metadata, diagrams of entity relationships, business processes, and process flows, for governance and reference.
• Ensure proper integration of data with existing standards and business processes to support smooth operations, maintaining consistency across systems.
• Create plans, test files, and scripts for data warehouse testing, including unit and integration testing to ensure system readiness.
• Develop, document, and deliver complex ad-hoc queries, consulting with business users to determine needs, feasibility, and priorities.
• Develop and implement ETL processes and map data between source systems, data warehouses, and data marts, ensuring smooth data flow across them, while verifying the structure, accuracy, and quality of warehouse data.

Senior Data Architect

• Develop technical enablement content, including presentations, solution guides, white papers, workshops, labs, and training materials.
• Design, build, and maintain product demonstrations that showcase customer challenges, technical capabilities, and business outcomes.
• Support field sales, systems engineering, and channel teams by providing technical expertise and creating customer-facing content.
• Deliver presentations at customer meetings, internal enablement sessions, partner events, and industry conferences.
• Collaborate closely with Product Management, Engineering, Marketing, and regional field organizations to support product launches and strategic initiatives.
• Stay current on emerging technologies and industry trends in data center networking, automation, AI, and cloud infrastructure.
• Translate complex technical concepts into clear, compelling messaging for technical and executive audiences.

Senior Technical Marketing Engineer – Apstra Data Center

• Design, build, and optimize robust ETLs using PySpark and DBT to process large-scale customer datasets.
• Define the technical vision for DC data architecture, mentor engineers, and manage external contractors to ensure the team delivers high-quality, practical solutions for current and future needs.
• Partner with product, engineering, and applied science teams to scope work and deliver data solutions that address real-world challenges in customer data quality and product feature requirements.

Staff Software Engineer – DC Tech Lead

• Design, build, and maintain robust data pipelines and data lake architecture for both batch and real-time streaming use cases, including high-volume, low-latency data processing
• Improve observability, alerting, and SLOs across data systems so pipelines are easier to monitor and issues are caught early
• Optimize ETL/ELT workflows for performance, scalability, and fault tolerance
• Develop dbt workflows to onboard Evaluation Partners and create end-of-day reporting for partner analysis
• Build and support event-driven architectures and scalable platform components
• Contribute to the orchestration and automation of workflows
• Integrate complex financial APIs and third-party data sources into internal systems
• Collaborate with analytics, product, and ML engineers to develop and deploy reliable data products
• Work on feature pipelines and model-ready data to support ML engineers
• Promote high standards in code quality, testing, and platform reliability
• Participate in Agile ceremonies and foster a collaborative, growth-oriented team culture

Senior Data Engineer

• Collaborate with other Engineers and Architects to define the enterprise data architecture roadmap.
• Drive the design and optimization of OLTP and OLAP models for scalability, performance, and maintainability.
• Establish standards for data modeling, storage, and integration across systems.
• Partner with other key stakeholders within engineering in developing a comprehensive data and BI strategy aligned with business objectives.
• Define data governance practices, data access control, compliance, and quality standards.
• Lead proof-of-concepts (POCs) for new data technologies and frameworks.
• Own the architectural review process and guidance to development teams on data-related projects.
• Establish and ensure best patterns and practices for ORM usage (Entity Framework and others) and SQL optimization, according to business needs.
• Evaluate and recommend where AI/ML can enhance data-driven decision-making.
• Stay current with modern data engineering trends, cloud-native architectures, and big data platforms.
• Actively participate and take ownership of Data Architecture artifacts via ADR process.
• Drive AI adoption by introducing and guiding teams in leveraging AI capabilities within the data engineering space to enhance internal efficiency, innovation, and decision-making in everyday workflows.
• Liaison between technology and product teams assisting teams in translating business requirements into tangible architectures that meet business needs now in and in the future.
• Design data architectures that accurately reflect and support evolving complex product and business processes and are required by our customer base.
• Lead data architecture initiatives, collaborating with cross functional teams, from concept through implementation, including governance and quality frameworks.
• Identify opportunities for predictive analytics and advanced modeling.
• Support and promote the company values through positive interactions with both internal and external stakeholders on a regular basis.
• Other strategic business initiatives or special cross-functional project involvement as required.

Data Architect

• Define and evolve enterprise data architecture principles, standards, and reference architectures aligned to business priorities and modern practices
• Lead the design and maintenance of enterprise conceptual, logical, and physical data structures, ensuring consistent definitions and shared semantics
• Establish domain-oriented architecture patterns for reusable, governed data products and interoperable data flows
• Develop architecture patterns supporting both batch and streaming workloads, including event-driven approaches and canonical representations
• Partner with data engineering teams to translate architecture and logical designs into scalable physical implementations on AWS cloud data platforms
• Ensure consistent data definitions, lineage, and metadata documentation across domains by enabling cataloging and lineage platforms
• Maintain a central repository of architecture artifacts, definitions, and metadata documentation
• Influence data design decisions across programs and projects through architecture reviews and standards enforcement
• Facilitate architecture and data design workshops with business and technical stakeholders
• Lead, mentor, and develop a team of data architects and specialists, ensuring consistent delivery of architecture outcomes
• Stay current on evolving architecture trends and evaluate their applicability to Deckers

Director, Data Architecture

• Perform Data Warehouse Architecture at an intermediate level
• Design and develop data models and ETL specifications
• Conduct data analysis and recommend solutions
• Participate in data warehouse and dashboard architecture planning
• Propose requirements, standards, and best practices for data modeling and ETL
• Conduct product and vendor research and present recommendations

IS Data Warehouse Architect II

• Serves as a lead in the analysis of business requirements associated with the design and implementation of highly complex, highly scalable enterprise data processes
• Designs and develops robust and efficient processes for extracting, loading and transforming data to meet the needs of enterprise scale projects
• Provides guidance and participates in activities involved in the analysis, design, development, troubleshooting, debugging and maintenance of an enterprise data management and data ecosystem
• Identifies, investigates, tracks, and resolves the most complex technical errors ensuring the solution is timely and of acceptable quality
• Establishes and enforces database standards, guidelines, procedures and quality assurance for database deliverables such as conceptual design, logical data model capacity planning, external data interface specs, data loading, data maintenance plan and security
• Reviews and analyzes data objects and models to improve data management and data access
• Designs, constructs, tests and implements extraction and transformation programs, processes and cycles for historical and current source data
• Creates technical specification for supporting enterprise data transformation processes and supplementing system documentation for ETL processes
• Performs data profiling, source-target mappings, data transformation development, optimization, testing and implementation
• This position participates and serves as a lead in maintaining the ETL environment for the company’s system-wide enterprise data warehouse.

Supply Chain Data Engineer

• Design, build, and maintain scalable ERP data pipelines for platforms such as Workday and enterprise systems
• Own end‑to‑end lifecycle of ERP data pipelines (ingestion → transformation → delivery)
• Support data conversion and migration initiatives (e.g., M&A, system integrations)
• Ensure pipeline reliability, recoverability, and stable production operations
• Troubleshoot pipeline failures and resolve root causes of data defects and operational issues
• Partner with business analysts and stakeholders to translate requirements into data solutions
• Implement and enforce SDLC best practices (version control, code reviews, CI/CD, release management)
• Develop and maintain data quality controls (freshness, completeness, anomaly detection, schema management)
• Detect and manage schema drift and downstream data issues proactively
• Build and maintain monitoring, alerting, and observability for data pipelines
• Optimize performance, scalability, and cost of data workloads
• Track operational KPIs (e.g., pipeline success rates, SLAs, incident trends, recovery times)
• Create runbooks, documentation, and audit‑ready operational processes
• Collaborate with data governance, security, and compliance teams on controls and data access
• Support analytics, reporting, and integration teams with reliable, well‑governed datasets
• Communicate effectively with technical and non‑technical stakeholders and escalate risks early

Senior ERP Data Engineer

• Evolving data infrastructure and data analytics capabilities
• Building architecturally-sound data systems and pipelines for analytics and data science
• Leading full stack development projects
• Collaborating with cross-functional teams
• Managing data logistics including specifications, transfers, and structures
• Accessing, extracting, and transforming data from various sources using tools like Hadoop, Spark, and SQL
• Supporting analytical proof of concepts and tool exploration
• Developing scalable ETL pipelines and ensuring data quality and reliability
• Assisting in Agile/Lean methodologies and DevOps practices

Data Engineer jobs in Utah

See all jobs on JobTailor

Junior Data Warehouse Engineer

Senior Software Engineer, Data

Senior Software Engineer, ERP, Data & Domain

Staff Data Engineer

Data Engineer

Data Engineer

Data Engineer II

Senior Data Architect

Senior Technical Marketing Engineer – Apstra Data Center

Staff Software Engineer – DC Tech Lead

Senior Data Engineer

Data Architect

Director, Data Architecture

IS Data Warehouse Architect II

Supply Chain Data Engineer

Senior ERP Data Engineer

Data Engineer