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# Lead Software Engineer, Databricks & Cloud

- **Company:** U.S. Bank
- **Location:** Atlanta, GA, United States
- **Experience:** Expert
- **Salary:** $133,365 - $156,900
- **Contract:** Permanent contract
- **Skills:** Unity 3d, Application Programming Interfaces (APIs), Artificial Intelligence, Airflow, Amazon Web Services, Amazon S3, Apache HTTP Server, Automation of Tests, Microsoft Azure, Cloud Computing, Cloud Database, Code Review, Continuous Integration, Data Architecture, Information Engineering, Extract Transform Load (ETL), Data Systems, Apache Hive, Identity and Access Management, Python (Programming Language), Power BI, Azure Data Lake, SQL Databases, Data Streaming, Tableau (Software), Datadog, Retrieval-Augmented Generation, Snowflake, Multi-Cloud, Git, Data Lakes, Pyspark, Collibra, Apache Kafka, Terraform, Software Version Control, Data Pipelines, Databricks
- **Published:** November 11, 2026
- **Apply:** https://dejobs.org/x/x/BB89050AE5934E6496C60CA50CA252F2/job/

## About the Role

* Bachelor's degree, or equivalent work experience
 * Six to eight years of relevant experience, * 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 ., * 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.

## 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., * 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.