Senior Cloud Data Architect & Databricks Engineer

US Bank; Cincinnati (OH); On-site; USD 125,000 - 170,000; Full time

Benefits offered by this job

Healthcare (medical, dental, vision)

401(k) plan

Paid vacation

Sick and Safe Leave

Paid holidays

Parental leave

Adoption assistance

Job summary

U.S. Bank is seeking an experienced architect to lead the design of scalable Databricks Lakehouse architectures. You will migrate Oracle SQL workloads to cloud data platforms, build high-volume ETL/ELT pipelines, and optimize performance across distributed data processing environments.

The role requires strong Python/PySpark skills, Delta Lake expertise, and collaboration with cloud, security, and application teams to deliver secure, scalable data solutions.

Qualifications

• Bachelor's degree or equivalent experience in a technical field.
• 7–9 years in technology architectural design, or 10+ years across disciplines.
• Proven hands-on Databricks and SQL/PLSQL expertise.

Responsibilities

• Design and implement scalable Databricks Lakehouse architectures.
• Develop data solutions using Databricks, Python, PySpark, and Delta Lake.
• Migrate Oracle SQL/PLSQL workloads to cloud-based data platforms.
• Design and implement high-volume ETL/ELT pipelines and data ingestion.
• Optimize Databricks performance, including SQL queries and compute utilization.
• Integrate Databricks with Oracle, AWS S3, and analytics platforms.
• Establish reusable data architecture and CI/CD standards.
• Collaborate with cross-functional teams to deliver scalable data solutions.

Skills

Databricks Lakehouse

Python

PySpark

SQL performance tuning

Orac le databases

ETL/ELT pipelines

CI/CD

Cloud data platforms

Education

Bachelor's degree or equivalent experience

Tools

Databricks

Delta Lake

Oracle SQL

AWS S3

Git

SQL tooling

Job description

U.S. Bank is seeking an experienced architect to lead the design of scalable Databricks Lakehouse architectures. You will migrate Oracle SQL workloads to cloud data platforms, build high-volume ETL/ELT pipelines, and optimize performance across distributed data processing environments.

The role requires strong Python/PySpark skills, Delta Lake expertise, and collaboration with cloud, security, and application teams to deliver secure, scalable data solutions.