AI Platform Data Engineer

Zions Bancorporation • Midvale, UT

2d • Hybrid

About The Position

Zions Bancorporation’s Enterprise Technology and Operations (ETO) team is 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 with the best experience possible for over 150 years. Help us transform our workforce of the future, today. As a Data Engineer on the AI Platform team, you will design, build, and maintain data pipelines, integrations, and models that power our GCP-based AI platform. You’ll work closely with engineering, data science, and AI teams to ensure data is accessible, reliable, and secure for advanced analytics and machine learning workloads. As an AI Platform Data Engineer, you will have the opportunity to: Develop, maintain, and optimize data pipelines and ETL/ELT processes using GCP services Integrate diverse internal and external data sources to support AI and analytics use cases. Implement data quality, validation, and monitoring processes to ensure accuracy and reliability. Collaborate with AI engineers, data scientists, and platform users to enable seamless access to training, inference, and production datasets. Support metadata management, data cataloging, and documentation for platform users. Data governance and security: Ensured data governance and compliance with industry standards and regulations through robust security practices and techniques Participate in evaluating new data engineering technologies and best practices for GCP. Contribute production-ready code for data services and integrations (primarily Python and SQL). Support MLOps workflows and job scheduling for machine learning and AI applications. Design and implement scalable data models across diverse storage paradigms (e.g., data lakes, lakehouses, and data warehouses), enabling efficient data processing, analytics, and machine learning workflows.

Requirements

• 4 years of experience in data engineering, with hands-on work designing and maintaining data pipelines and integrations on cloud platforms.
• Bachelors degree in Computer Science, Computer Engineering or related field. A combination of education and experience may meet qualifications.
• Demonstrated expertise in distributed systems and advanced programming: Developed production-grade solutions in Python and/or 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 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.
• Familiarity with orchestration frameworks (e.g., Airflow, Databricks Workflows, Control-M) for scheduling and managing data workflows.
• 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.
• Knowledge of data quality, validation, and monitoring best practices.
• Understanding of data security, privacy, and compliance in a cloud environment.
• Excellent communication and collaboration skills, with experience working alongside AI engineers and data scientists.

Nice To Haves

• Experience with GCP Vertex AI or other agent building platforms/services.

Responsibilities

• Develop, maintain, and optimize data pipelines and ETL/ELT processes using GCP services
• Integrate diverse internal and external data sources to support AI and analytics use cases.
• Implement data quality, validation, and monitoring processes to ensure accuracy and reliability.
• Collaborate with AI engineers, data scientists, and platform users to enable seamless access to training, inference, and production datasets.
• Support metadata management, data cataloging, and documentation for platform users.
• Data governance and security: Ensured data governance and compliance with industry standards and regulations through robust security practices and techniques
• Participate in evaluating new data engineering technologies and best practices for GCP.
• Contribute production-ready code for data services and integrations (primarily Python and SQL).
• Support MLOps workflows and job scheduling for machine learning and AI applications.
• Design and implement scalable data models across diverse storage paradigms (e.g., data lakes, lakehouses, and data warehouses), enabling efficient data processing, analytics, and machine learning workflows.

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

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Number of Employees: 5,001-10,000 employees