Data DevOps Analyst

Children's Hospital Association•Lenexa, KS

2d•Hybrid

About The Position

The Data DevOps Analyst is responsible for the support, maintenance, development, and deployment of CHA’s data pipeline and data visualization platforms and related applications. This role oversees release management activities, including upgrades, installations, configuration, and administration across data and analytics environments and their interfacing systems. Additionally, the DevOps Engineer designs, builds, and maintains data pipelines and ETL workflows to support reliable, scalable, and secure analytics solutions. Administer Tableau environments across multiple sites, ensuring security standards, access controls, permissions, and configurations are consistently applied. Oversee production change control processes for all data‑related applications. Proactively monitor system health and performance, investigate and resolve failures, identify trends, and tune systems to prevent potential issues. Manage and maintain external data source integrations with Tableau to ensure reliable data refresh and connectivity. Provide administrative and technical support for legacy environments, including upgrades, patching, configuration, and security administration. Respond to and resolve customer support tickets, coordinating with stakeholders to ensure timely issue resolution. Design and develop data ingestion and ETL pipelines, automating processes to improve reliability and operational efficiency. Monitor scheduled ETL workflows; proactively diagnose and resolve complex failures, performance issues, and data inconsistencies Compile, validate, and organize data sets to support business reporting requests and project requirements. Participate in peer reviews, unit testing, data validation, and troubleshooting to ensure accuracy, performance, and reliability of data pipelines.

Requirements

Bachelor’s degree in computer science, or STEM related field is preferred, or an equivalent combination of education, training, and experience.
Minimum of three years of experience in data management and/or system engineering.
Solid understanding of software development principles and coding best practices.
Strong working knowledge of SQL and relational database management systems.
Hands‑on experience with Windows‑based server installation and administration, including a solid understanding of Windows Server operating systems, security concepts, and computer networking.
Experience with cloud computing platforms.
Experience working within SDLC and DevOps practices, including use of code repositories.
Strong interpersonal, communication, and problem‑solving skills in a team‑based development environment.

Nice To Haves

Exposure to data visualization tools.
Experience working with healthcare data.
Experience working with Microsoft Azure and Azure Data Factory.

Responsibilities

Support, maintenance, development, and deployment of CHA’s data pipeline and data visualization platforms and related applications.
Oversee release management activities, including upgrades, installations, configuration, and administration across data and analytics environments and their interfacing systems.
Design, build, and maintain data pipelines and ETL workflows to support reliable, scalable, and secure analytics solutions.
Administer Tableau environments across multiple sites, ensuring security standards, access controls, permissions, and configurations are consistently applied.
Oversee production change control processes for all data‑related applications.
Proactively monitor system health and performance, investigate and resolve failures, identify trends, and tune systems to prevent potential issues.
Manage and maintain external data source integrations with Tableau to ensure reliable data refresh and connectivity.
Provide administrative and technical support for legacy environments, including upgrades, patching, configuration, and security administration.
Respond to and resolve customer support tickets, coordinating with stakeholders to ensure timely issue resolution.
Design and develop data ingestion and ETL pipelines, automating processes to improve reliability and operational efficiency.
Monitor scheduled ETL workflows; proactively diagnose and resolve complex failures, performance issues, and data inconsistencies.
Compile, validate, and organize data sets to support business reporting requests and project requirements.
Participate in peer reviews, unit testing, data validation, and troubleshooting to ensure accuracy, performance, and reliability of data pipelines.