Infrastructure Analytics Engineer: Data, Automation & Cloud

Us Bank; Hopkins (MN); On-site; USD 105,000 - 124,000; Full time

Benefits offered by this job

Healthcare

Life Insurance

Disability Insurance

Parental Leave

401(k) Plan

Paid Vacation

Paid Holidays

Adoption Assistance

Sick Leave

Job summary

U.S. Bank is seeking an Infrastructure Data Analytics Engineer to ingest, transform, and analyze data from infrastructure, cloud, and enterprise systems. You will build scalable ETL/ELT pipelines, write complex SQL and Python, and create Alteryx workflows to automate analytics tasks.

Responsibilities include analytics, reporting, and partnering with leadership to translate technical findings into business insights, while following SDLC, DevOps, and governance practices.

Qualifications

• Bachelor's degree in a related field or equivalent work experience.
• Five to seven years of statistical and/or data analytics experience.

Responsibilities

• Acquire, transform, integrate, and analyze data from infrastructure, platform, cloud, and enterprise systems.
• Develop SQL queries, Python, and Alteryx workflows to support analytics and automation.
• Create dashboards and reports to support executive decision making.
• Design and maintain ETL/ELT pipelines and data models.
• Follow SDLC practices, version control, and CI/CD in a DevOps environment.
• Ensure data governance, security, and compliance across analytics assets.

Skills

SQL (Advanced)

Python

Alteryx

Power BI

Excel

Education

Bachelor's degree or equivalent experience

Tools

Azure

AWS

Databricks

Snowflake

Datadog

Splunk

Dynatrace

ServiceNow

GitHub / GitLab / Azure DevOps

CI/CD tooling

Job description

U.S. Bank is seeking an Infrastructure Data Analytics Engineer to ingest, transform, and analyze data from infrastructure, cloud, and enterprise systems. You will build scalable ETL/ELT pipelines, write complex SQL and Python, and create Alteryx workflows to automate analytics tasks.

Responsibilities include analytics, reporting, and partnering with leadership to translate technical findings into business insights, while following SDLC, DevOps, and governance practices.