AI Cloud Data Engineer
About The Position
UMB’s Artificial Intelligence (AI) team is responsible for driving automation, data-driven decision making and software modernization using AI centric tools. Currently, we leverage machine learning, natural language processing, predictive analytics, and generative AI to enhance customer experience, and improve operational efficiency. This includes utilizing fraud protection software to ensure regulatory and system availability. As AI Cloud Data Engineer, you will be responsible designing, building, and optimizing cloud-based data pipelines and platforms that support enterprise AI/ML workloads. This role combines cloud engineering and data engineering expertise to deliver secure, scalable, and compliant data solutions in hybrid and multi-cloud environments. The AI Cloud Data Engineer works closely with architects, data scientists, and application teams to ensure data quality, governance, and performance for AI-driven initiatives across payments, fraud detection, compliance, and customer experience. This is a subset of the overall responsibilities which will include multiple initiatives as assigned by IT leadership. This role is hybrid (Mon through Thu on-site / Fri remote) for candidates in the Kansas City metropolitan area and open to qualified remote candidates outside of the Kansas City area but only within the US.
Requirements
- You have a Bachelor’s degree in Computer Science, Data Engineering, Cloud Computing, or related field and at least 3 years of experience in cloud data engineering or enterprise data integration, OR equivalent combination of education and work experience.
- You have proficiency with at least one major cloud platform (AWS, Azure, GCP).
- You have experience with SQL and programming languages such as Python, Scala, or Java.
- You have familiarity with containerization and orchestration (Docker, Kubernetes).
- You have expertise in data pipeline frameworks (Apache Spark, Kafka, Flink, Dataflow).
- You have knowledge of cloud-native data services (AWS Redshift, Glue, Snowflake, BigQuery, Azure Synapse).
- You have familiarity with MLOps and integrating data workflows with AI model lifecycle.
- You have strong understanding of data governance, lineage, and metadata management.
- You have the ability to design fault-tolerant, secure, and scalable data workflows in the cloud.
Nice To Haves
- You have a Master’s degree in Data Science, Cloud Engineering, or related discipline and at least 5 years of experience in cloud data engineering within financial services or regulated industries.
- You have any of the following certifications: AWS Certified Data Analytics Specialty, Google Professional Data Engineer, or Microsoft Azure Data Engineer Associate.
- You have experience with regulatory reporting and AI-ready data pipelines.
- You have a background in high-volume financial data systems or real-time payments.
- You have hands-on experience with Lakehouse technologies (Delta Lake, Apache Iceberg, Hudi).
- You have knowledge of distributed data architectures and data mesh patterns.
- You have familiarity with AI observability tools and data drift monitoring.
- You have experience with privacy-preserving technologies and secure data-sharing frameworks.
- You have deep understanding of cloud cost optimization for data-intensive AI workloads.
Responsibilities
- Design and develop cloud-native data pipelines to support AI/ML training, validation, and inference.
- Build and optimize data lakes, warehouses, and lakehouse environments (e.g., Delta Lake, Apache Iceberg) in the cloud.
- Collaborate with AI Data Architect and AI Cloud Architect to ensure data platforms meet enterprise standards.
- Automate ETL/ELT workflows and orchestration using tools such as Airflow, Glue, and Dataflow.
- Ensure compliance with financial data security, governance, and regulatory requirements (GLBA, GDPR, OCC, FFIEC).
- Integrate structured, unstructured, and streaming data sources from banking systems, payment hubs, and customer channels.
- Implement monitoring and observability solutions for cloud-based data pipelines.
- Optimize data workflows for performance, scalability, and cost efficiency in cloud environments.
- Support disaster recovery, resiliency, and data availability strategies for AI platforms.
- Troubleshoot data pipeline, integration, and cloud deployment issues.
Benefits
- UMB offers competitive and varied benefits to eligible associates, such as Paid Time Off; a 401(k) matching program; annual incentive pay; paid holidays; a comprehensive company sponsored benefit plan including medical, dental, vision, and other insurance coverage; health savings, flexible spending, and dependent care accounts; adoption assistance; an employee assistance program; fitness reimbursement; tuition reimbursement; an associate wellbeing program; an associate emergency fund; and various associate banking benefits.
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
