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# Sr Data Warehouse Analyst

- **Company:** U.S. Bank
- **Location:** Englewood, CO, United States
- **Experience:** Expert
- **Salary:** $105,400.0 - $124,000.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Airflow, Amazon Web Services, Microsoft Azure, Databases, Continuous Integration, Information Engineering, Data Governance, Data Integration, Extract Transform Load (ETL), Data Warehousing, IBM InfoSphere DataStage, DevOps, Distributed Data Store, Github, Python (Programming Language), Meta-Data Management, SQL Databases, Unstructured Data, Google Cloud, Data Storage Technologies, System Availability, Apache Spark, Git, Data Lakes, Data Management, GPT, Data Pipelines, Databricks
- **Published:** August 29, 2026
- **Apply:** https://www.techcareers.com/job.asp?id=3369523266&tx=JT989TYI&pt=1&aff=0B19D771-A501-4A5E-8338-2A822B784D54&utm_source=Job%20Feed&utm_medium=textkernel&utm_campaign=DE&utm_term=0B19D771-A501-4A5E-8338-2A822B784D54

## About the Role

Bachelor's degree or equivalent work experience

-At least 5 years experience with tools, facilities and techniques for managing and administering data.

Preferred Skills/Experience

 * Hands on experiencein Data Engineering, Data Warehousing, ETL/ELT Development, Data Integration, or Data Management roles.
 * Advancedproficiencyin SQL withhands-onexperienceindatamodeling,databasedesign,queryoptimization,andperformancetuning.
 * Strongprogrammingexperiencewith Python fordataprocessing,automation,orchestration,andengineeringsolutions.
 * Experiencedesigningandsupportingmodern Data Warehouse, Data Lake, Lakehouse, and distributed data architectures .
 * Hands-onexperiencewithatleastonemajorcloudplatform: AWS, Microsoft Azure, or Google Cloud Platform (GCP) .
 * Experiencedevelopingscalable ETL/ELT pipelines usingSQL,Python,cloud-nativeservices,andenterpriseintegrationtools.
 * Knowledgeofmodernbigdataandorchestrationtechnologiessuchas Apache Spark, Databricks, Airflow, or related platforms .
 * Experiencewith Git, GitHub, Azure DevOps, CI/CD pipelines, and DevOps best practices fordataengineering.
 * Understandingof data governance, data quality, security, privacy, compliance, and metadata management principles.
 * Familiaritywith AI-assisted development tools suchasGitHubCopilot,ChatGPT,Claude,orsimilarproductivitysolutions,alongwithstronganalytical,problem-solving,communication,andstakeholdermanagementskills.

## Description

* Design,develop,andmaintainenterprise-scale Data Warehouse, Data Lake, and Lakehouse solutionssupportingoperationalreporting,analytics,andAI/MLinitiatives.
 * Buildandenhancescalable data models, database architectures, and data storage frameworks tosupportbusiness,analytical,andoperationalrequirements.
 * Develop,optimize,andsupport batch, streaming, and near real-time ETL/ELT pipelines usingSQL,Python,cloud-nativeservices,andmoderndataintegrationtechnologies.
 * Integrate,transform,andmanage structured, semi-structured, and unstructured data frommultipleinternalandexternaldatasourceswhileensuringdataqualityandreliability.
 * Implementandsupportenterprisedataintegrationsolutionsutilizing Informatica, IBM DataStage, or similar ETL/data integration platforms .
 * Partnerwithbusinessstakeholders,analysts,architects,andapplicationteamstogatherrequirementsanddeliverscalable,high-performingdatasolutions.
 * Enable business intelligence, advanced analytics, and AI/ML use cases bypreparing,optimizing,andgoverningdatasetsforenterpriseconsumption.
 * Monitor,troubleshoot,andtunedataplatformsandpipelinestoensure high availability, performance, scalability, automation, and operational excellence .
 * Implementandsupportcloud-baseddatasolutionsleveraging AWS, Microsoft Azure, or Google Cloud Platform (GCP) services.
 * Applyenterprisestandardsfor data governance, security, privacy, compliance, and metadata management toprotectorganizationaldataassets.


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