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
Lead the design and delivery of scalable, governed data products on a Databricks Lakehouse across Azure and AWS . This hands-on technical leadership role will help advance Business Banking’s transition to Databricks by providing direction across engineering, product, architecture, and governance teams and delivering trusted data for analytics, reporting, and AI use cases.
Key Responsibilities
Lead and guide Databricks data engineering across Bronze, Silver, and Gold layers, with particular focus on trusted, reusable Silver and Gold data products .
Translate business requirements into scalable data architecture, engineering designs, delivery standards, and technical acceptance criteria.
Remain hands-on in engineering and development, including coding, code review, and code management , while guiding the delivery of batch, CDC, streaming, API, and file-based data pipelines.
Review data models, solution designs, and critical code for quality, security, scalability, performance, and alignment with engineering standards.
Drive cross-cloud data integration and sharing across Azure, AWS, Databricks, and Snowflake.
Embed data quality, lineage, governance, PII and PCI controls, monitoring, and reliability into data solutions.
Establish engineering best practices for CI/CD, testing, source control, deployment, and observability.
Provide technical leadership through influence across distributed onshore, offshore, and GCC engineering teams, establishing clear standards and guiding delivery without direct people-management responsibility .
Partner with product, architecture, governance, platform, and business stakeholders to resolve technical dependencies, risks, and delivery challenges.
Basic Qualifications
Bachelor’s degree, or equivalent work experience
Six to eight years of relevant experience
Required Skills
Strong hands-on experience with Python, PySpark, SQL , Spark SQL, and ETL/ELT development.
Hands-on expertise with Databricks, Delta Lake, Unity Catalog, medallion architecture , and Databricks Workflows/Lakeflow.
Experience building batch, CDC, streaming, API, and file-based pipelines, including Kafka or Azure Event Hubs.
Strong cloud data engineering experience with Azure and/or AWS , including experience with services such as ADLS Gen2, Data Factory, S3, IAM, and related technologies.
Knowledge of Snowflake, Delta Sharing, Delta UniForm, Apache Iceberg, and cross-cloud data sharing.
Experience with data modeling, Power BI/DAX, data quality, governance, lineage, and PII/PCI controls.
Strong knowledge of Git, CI/CD, automated testing, technical design, architecture reviews, and engineering best practices.
Demonstrated ability to provide technical direction, code review, and engineering guidance across distributed teams through influence rather than direct authority .
Preferred Qualifications
Experience working across multi-cloud environments.
Experience with Terraform, Apache Airflow, Datadog, Collibra, Tableau, or Databricks Metric Views.
Experience supporting AI/RAG or advanced analytics data use cases.
Banking, financial services, or other regulated-industry experience.
Experience working with Business Banking or commercial banking data products.
Databricks, Snowflake, Azure, or AWS certifications.
Location Expectation
This role requires working from a U.S. Bank location three (3) or more days per week.
If there’s anything we can do to accommodate a disability during any portion…