Staff Data Engineer

Zions Bancorporation•Midvale, UT

10h•Hybrid

About The Position

Zions Bancorporation’s Enterprise Technology and Operations (ETO) team is transforming what it means to work for a financial institution. With a commitment to technology and innovation, we have been providing our community, clients and colleagues the best experience possible for over 150 years. We are looking for a highly experienced Staff Data Engineer that has a proven track record of leading the end-to-end migration of on-premise data warehouse systems to modern cloud-based data platforms (e.g., AWS, GCP, Azure). In this role, you will partner with our Architecture, Data Engineering, and Technology Enablement teams to design and build new data solutions.

Requirements

10+ years of data engineering development experience.
Bachelor’s degree in computer science, computer engineering, or related field. A combination of education and experience may meet requirements.
Proven track records in successfully migrating large scale data warehouse from on-premises to the cloud.
Deep experience with the design and management of scalable data pipelines and workflows.
Built robust ETL/ELT processes using Databricks Workflows, Kafka, and modern ELT tools.
Champion CI/CD and automated testing best practices to ensure reliability, maintainability, and rapid deployment.
Demonstrated expertise in distributed systems and advanced programming.
Developed production-grade solutions in Python and PySpark, leveraging performance optimization techniques such as partitioning, caching, parallelism, and efficient data formats.
Optimized cloud infrastructure for cost and performance.
Led cost-efficient Spark workload strategies on Databricks by right-sizing clusters (e.g., on-demand drivers, spot/preemptible workers), enabling autoscaling and auto-termination, and utilizing job compute, serverless clusters, cluster pools, tagging, and budget controls.
Architected and led scalable data platforms.
Designed high-throughput, distributed data systems including data lakes and warehouses.
Applied strong OLTP/OLAP modeling principles to support both real-time and analytical workloads.
Deep understanding of cloud platforms, cloud-native technologies (e.g., Kubernetes, Docker), and infrastructure-as-code (IaC) practices.
Extensive expertise in managing both cloud and on-premises environments, with strong focus on seamless data and file movement between cloud and on-premises systems to ensure efficient and secure data integration.
Ensured data governance and compliance with industry standards and regulations through robust security practices and techniques.
Demonstrated ability to mentor and coach engineers and collaborate effectively with cross-functional teams and facilitate clear communication across the organization.
Ability to produce comprehensive technical documentation.

Nice To Haves

Google Cloud preferred

Responsibilities

Contribute to the technical strategy, roadmap, and architectural design of software systems.
Demonstrate strong analytical, organizational, problem-solving skills and the ability to implement solutions independently.
Develop and maintain scalable applications using data engineering technologies.
Creates and manages CI/CD pipelines for automated deployments.
Mentor and guide engineers on technical aspects of cloud and data development.
Coordinate efforts across multiple teams and departments.
Lead and facilitate technical discussions and presentations.
Actively engage in engineering community channels and events.
Act as a technical advisor and reviewer for critical projects.
Demonstrate emotional intelligence and empathy when interacting with others.