Senior Data Engineer

ATL Technology

. Design, build, and maintain scalable data pipelines and data integration patterns using Microsoft Azure and Microsoft Fabric .

Posted 10/23/2026full-timeSpringville • Utah • United StatesSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and maintaining scalable data pipelines using Microsoft Azure and Microsoft Fabric, with a strong focus on data quality, governance, and integration across enterprise platforms. Proven ability to lead data engineering initiatives, mentor team members, and drive DataOps practices to enhance operational efficiency and business outcomes.

Highest-signal resume keywords

Data Pipeline DevelopmentMicrosoft Azure Data ServicesSQL and Python ProficiencyData Quality ImplementationDataOps Practices

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

ETL/ELT DesignData ModelingPerformance TuningOrchestrationMonitoringAPI-Based IntegrationsDimensional ModelingData GovernanceAutomationPredictive Analytics

Soft Skills

Strong Communication SkillsIndependent Decision-MakingCollaboration with StakeholdersMentoringProblem-Solving

Tools & Technologies

Azure Data FactoryAzure Data LakeSynapse AnalyticsPower BIAzure DevOpsMicrosoft FabricGit-Based Source ControlMicrosoft PurviewMDMData Cataloging

Certifications & Qualifications

Microsoft Certified: Azure Data Engineer AssociateMicrosoft Fabric Analytics Engineer AssociateRelevant Azure CertificationsPower BI Certifications

Industry Keywords

ERP IntegrationManufacturingMedical DeviceLife SciencesRegulated IndustryKimball MethodologyAI Use CasesMachine LearningData GovernanceOperational Support

Tech Stack

Tools & technologies

AzureCloudERPETLPythonSQL

About the role

Key responsibilities & impact

Design, build, and maintain scalable data pipelines and data integration patterns using Microsoft Azure and Microsoft Fabric
Develop ingestion, transformation, orchestration, monitoring, and deployment standards for enterprise data workloads
Build and mature ATL’s Bronze, Silver, and Gold data layers with reusable, well-documented engineering practices
Drive platform reliability, observability, performance optimization, and operational support practices
Integrate data from Infor ERP, Workday, Autodesk Fusion, Dynamics CRM, SharePoint, manufacturing systems, and future enterprise platforms
Develop API-based and connector-based integrations where appropriate
Partner with application owners and business stakeholders to understand source system logic, data definitions, and integration requirements
Monitor pipeline health and proactively resolve data integration issues
Design curated datasets and analytical models for Power BI and enterprise reporting
Support dimensional modeling and business logic for certified data assets
Partner with Finance, Operations, Quality, Engineering, Sales, and leadership teams to translate business needs into reliable data products
Enable governed self-service analytics by delivering trusted, consistent, and reusable data assets
Implement data quality checks, reconciliation controls, lineage, metadata, documentation, and issue resolution practices
Support master data and data governance initiatives in partnership with business data owners and stewards
Design data solutions supporting ATL’s regulated environment, including quality, privacy, security, and compliance considerations
Promote DataOps practices including source control, testing, CI/CD, and release discipline
Create reliable data foundations for AI, Copilot, automation, and advanced analytics initiatives
Identify opportunities to automate manual reporting and operational data processes
Support future predictive analytics and machine learning use cases through well-structured, governed data assets
Serve as a senior hands-on technical leader for ATL’s enterprise data platform
Partner with external consulting partners while building ATL’s long-term internal capability
Mentor future data engineering team members and help establish standards for the data engineering discipline
Influence architecture, tooling, and roadmap decisions with a practical business-outcome mindset

Requirements

What you’ll need

7+ years of data engineering experience, including experience building or significantly maturing enterprise data platforms
Strong hands-on experience with SQL, Python, ETL/ELT design, data modeling, and enterprise integration patterns
Experience with Microsoft Azure data services, including Azure Data Factory, Azure Data Lake, Synapse Analytics and/or Microsoft Fabric
Experience supporting global, multi-site organizations and working directly with business stakeholders
Strong communication skills with the ability to explain technical concepts clearly to both technical and non-technical audiences
Demonstrated ability to operate independently, make sound technical decisions, and connect platform work to business outcomes
Required experience in data pipeline development, orchestration, monitoring, performance tuning, and data quality implementation
Required experience with Git-based source control and CI/CD or DataOps practices using Azure DevOps or similar tooling
Bachelor's degree in Computer Science, Data Engineering, Information Systems, Engineering, or a related field preferred
Equivalent practical experience will be considered in lieu of a degree
Microsoft Certified: Azure Data Engineer Associate preferred
Microsoft Fabric Analytics Engineer Associate preferred
Relevant Azure, Power BI, data governance, or cloud architecture certifications are a plus
Preferred: Infor CSI/Syteline or other ERP integration experience
Preferred: manufacturing, medical device, life sciences, or regulated industry experience
Preferred: Power BI semantic models, dimensional modeling, Kimball methodology, Microsoft Purview, MDM, or data cataloging experience
Preferred: experience enabling AI, machine learning, or Copilot use cases through trusted enterprise data