Sr. Data Engineer

UMB Bank•Kansas City, MO

9d•$117,900 - $173,393

About The Position

The Enterprise Data Warehouse & Analytics team supports the data warehouse environment and analytics tools, giving business leaders access to business intelligence data to develop organizational growth strategies. The Sr. Data Engineer implements Snowflake cloud strategies, modernizes legacy systems, builds real-time reporting solutions, and develops future-facing data processing solutions using technologies including AWS, Confluent Kafka, Aurora PostgreSQL, Snowflake, Matillion, and Informatica. The role also supports multiple initiatives assigned by IT leadership. The position focuses on designing and maintaining cloud data pipelines and data platforms; building streaming and ETL solutions; developing and optimizing database structures and processing workflows; implementing data governance and lifecycle-management practices; and mentoring team members in collaboration with the senior architect. The role also evaluates and translates data to identify anomalies, trends, and correlations, and establishes organizational models and standards for data collection, storage, arrangement, and use.

Requirements

Bachelor’s degree in Information Technology and at least 5 years of experience in a technical role supporting and designing application technologies, or at least 8 years of relevant work experience in such a role.
At least 5 years of cloud data development or engineering experience, specifically with Azure or AWS, including hands-on experience deploying and managing Snowflake data platforms.
At least 5 years of experience with data pipeline development and business intelligence implementations.
Subject matter expertise in modern data platform architectures, including Apache Kafka for streaming, PostgreSQL database management, and Precisely for data integration and replication.
Business-first mindset, comfort with change, and passion for learning and using modern technologies, databases, code sets, and integration best practices.
Legal authority to work in the United States; work visa sponsorship is not available.

Nice To Haves

Banking or financial services industry experience.

Responsibilities

Design, build, and maintain cloud data pipelines, architecture, and datasets for ETL and real-time streaming using Kafka, Precisely, and Snowflake structures.
Build and optimize PySpark ETL jobs for S3-to-Aurora data loading using metadata-driven mappings and field validation, and collect performance metrics.
Develop and maintain AWS Lambda functions and EventBridge schedules and rules to orchestrate pipeline workflows, track operational status, and send alerts.
Develop and optimize Aurora PostgreSQL schemas, stored procedures, real-time and batch-load processes, indexes, and queries; troubleshoot database and data-processing issues.
Build and manage high-performance relational database structures, focusing on PostgreSQL replication, optimization, and real-time reporting pipelines.
Implement data governance and lifecycle-management strategies, including policies and automated approaches, and organizational models for overseeing data collection, storage, and utilization.
Design and support Kafka topics, partitions, retention policies, and access controls to meet data-volume and availability requirements.
Build and maintain Kafka producers and consumers that reliably publish and process events while preserving key-based ordering where required.
Mentor team members in collaboration with the senior architect, applying cloud expertise to modernize technologies and evaluate complex data trends.
Evaluate and translate data, identifying anomalies, trends, and correlations among similar datasets.
Create models and standards governing which data is collected, how it is stored and arranged, and how it is used in data systems and within the organization.