Staff Data Engineer at Zions Bancorporation

Midvale, Utah, United States -

Full Time

Start Date

Immediate

Expiry Date

10 Jun, 26

Salary

0.0

Posted On

12 Mar, 26

Experience

10 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Warehouse Migration, Cloud Platforms, Data Engineering, ETL/ELT, Databricks Workflows, Kafka, CI/CD, Python, PySpark, Spark Optimization, Data Lakes, Data Warehouses, OLTP/OLAP Modeling, Kubernetes, Docker, Infrastructure-as-Code

Industry

Banking

Description

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. Help us transform our workforce of the future, today. 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. Key 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. Qualifications: 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 (Google Cloud preferred), 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. Data governance and security: 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. Location: This position has a hybrid work from home schedule with a minimum of three days per week in the office at the new Zions Technology Center in Midvale, UT. The Zions Technology Center is a 400,000-square-foot technology campus in Midvale, Utah. Located on the former Sharon Steel Mill superfund site, the sustainably built campus is the company’s primary technology and operations center. This modern and environmentally friendly technology center enables Zions to compete for the best technology talent in the state while providing team members with an exceptional work environment with features such as: Electric vehicle charging stations and close proximity to Historic Gardner Village UTA TRAX station. At least 75%25 of the building is powered by on-site renewable solar energy. Access to outdoor recreation, parks, trails, shareable bikes and locker rooms. Large modern cafe with a healthy and diverse menu. Healthy indoor environment with ample natural light and fresh air. LEED-certified sustainable building that features include the use of low VOC-emitting construction materials. Benefits: Medical, Dental and Vision Insurance - START DAY ONE! Life and Disability Insurance, Paid Parental Leave and Adoption Assistance Health Savings (HSA), Flexible Spending (FSA) and dependent care accounts Paid Training, Paid Time Off (PTO) and 11 Paid Federal Holidays 401(k) plan with company match, Profit Sharing, competitive compensation in line with work experience Mental health benefits including coaching and therapy sessions Tuition Reimbursement for qualifying employees Employee Ambassador preferred banking products Apply now if you have a passion for impactful outcomes, enjoy working collaboratively with co-workers, and want to make a difference for the clients and communities we serve.

Responsibilities

This role involves contributing to the technical strategy, roadmap, and architectural design of software systems, focusing on designing and building new data solutions in partnership with cross-functional teams. Key duties include developing scalable applications, creating CI/CD pipelines, and mentoring other engineers on cloud and data development aspects.