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 & Integration Design and develop data ingestion processes from multiple sources, including:
Infrastructure monitoring platformsCMDB and asset management systems

Cloud platforms (Azure, AWS)
Enterprise databases REST and GraphQL APIsSaaS and third-party technology platforms

Build 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 & Transformation Develop complex SQL queries, stored procedures, views, and data models.

Create Python-based solutions for:
Data extraction

Data transformation

Data quality validation

Automation workflowsAPI integrations

Design 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 & Reporting Analyze infrastructure and operational data to identify:
Trends Risks Performance  issues

Capacity constraints

Optimization opportunities

Support 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 Development Develop 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, Dev Ops & Release Management Follow established Software Development Lifecycle (SDLC) methodologies including Agile delivery practices.

Maintain source code in approved repositories (Git Hub, Git Lab, Azure Dev Ops, 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 & Compliance Ensure…