Infrastructure Data Analytics Engineer

At U.
S. Bank, we’re on a journey to do our best. Helping the customers and businesses we serve to make better and smarter financial decisions and enabling the communities we support to grow and succeed. We believe it takes all of us to bring our shared ambition to life, and each person is unique in their potential. A career with U.
S. Bank gives you a wide, ever-growing range of opportunities to discover what makes you thrive at every stage of your career. Try new things, learn new skills and discover what you excel at—all from Day One.

Job Description
The Infrastructure Data Analytics Engineer is responsible for acquiring, transforming, integrating, and analyzing data from infrastructure, platform, cloud, and enterprise technology systems. This role combines data engineering, analytics, automation, and operational intelligence to provide actionable insights that support technology strategy, operational excellence, risk management, and executive decision making.
The ideal candidate possesses strong technical skills in SQL, Python, Alteryx, API integration, and data transformation while adhering to software development lifecycle (SDLC) practices, including source code management, testing, deployment, and release management.

Key Responsibilities
Data Acquisition & IntegrationDesign and develop data ingestion processes from multiple sources, including: Infrastructure monitoring platformsCMDB and asset management systemsCloud platforms (Azure, AWS)Enterprise databasesREST and GraphQL APIsSaaS and third-party technology platformsBuild and maintain scalable ETL/ELT pipelines to acquire, cleanse, transform, validate, and enrich data.
Integrate structured and unstructured data from disparate technology systems into centralized analytics platforms.
Automate recurring data collection and processing activities.
Data Engineering & TransformationDevelop complex SQL queries, stored procedures, views, and data models.
Create Python-based solutions for: Data extractionData transformationData quality validationAutomation workflowsAPI integrationsDesign and maintain Alteryx workflows for data preparation, blending, and analytics automation.
Implement reusable transformation frameworks and standardized data processing patterns.
Perform data reconciliation and data quality assurance activities.
Analytics & ReportingAnalyze infrastructure and operational data to identify: TrendsRisksPerformance issuesCapacity constraintsOptimization opportunitiesSupport executive reporting, operational scorecards, and KPI dashboards.
Translate technical findings into business-friendly recommendations and insights.
Partner with infrastructure, engineering, operations, and leadership teams to support data-driven decision making.
Automation & API DevelopmentDevelop API integrations between internal and external platforms.
Build automated workflows that reduce manual effort and improve data timeliness.
Support near real-time and batch data processing requirements.
Create reusable libraries and utilities that accelerate analytics delivery.
SDLC, DevOps & Release ManagementFollow established Software Development Lifecycle (SDLC) methodologies including Agile delivery practices.
Maintain source code in approved repositories (GitHub, GitLab, Azure DevOps, etc.).
Utilize branching, pull request, peer review, and merging standards.
Develop and maintain CI/CD deployment pipelines.
Create and maintain technical documentation, runbooks, and deployment procedures.
Participate in release planning, change management, testing, and production deployments.
Ensure appropriate version control, auditability, and governance of analytics assets and code.
Support incident management and post-release validation activities.
Governance & ComplianceEnsure adherence to enterprise data governance, security, and compliance requirements.
Maintain data lineage and metadata documentation.
Implement controls for data quality, access management, and operational resiliency.
Support regulatory and audit requests related to analytics solutions.
Basic QualificationsBachelor's degree in a related field, or equivalent work experienceFive to seven years of statistical and/or data analytics experiencePreferred QualificationsExperience analyzing infrastructure, cloud, or operational technology data.
Experience with Power BI, Tableau, or similar visualization platforms.
Experience with Azure, AWS, Databricks, Snowflake, or enterprise data platforms.
Knowledge of Infrastructure Observability and Monitoring platforms (Datadog, Splunk, Dynatrace, ServiceNow, etc.).
Experience with CI/CD tools and release automation.
Understanding of data governance, metadata management, and data quality frameworks.
Experience supporting enterprise-scale transformation or modernization programs.
Technical SkillsProgramming & AnalyticsSQL (Advanced)PythonAlteryxPower BIExcelData & IntegrationREST APIsJSON / XMLETL / ELTData ModelingData Quality ManagementDevOps & SDLCGitHub / GitLab / Azure DevOpsVersion ControlCI/CD PipelinesRelease ManagementTes