Data Engineers

Shirley Ryan AbilityLab•Chicago, IL

17h•Hybrid

About The Position

Data Engineers for Chicago, IL location. Develop secure, stable, scalable long-term plans for the flow of hospital data. Assist in the development of scalable data infrastructure and platforms to collect and process large amounts of data, including structured and unstructured data for analysis by clinical, research, and business resources. Establish methods and procedures for tracking data quality, completeness, redundancy, compliance and improvement. Create strategies and plans for data capacity planning, data security, life cycle data management, scalability, backup and archiving. Help oversee mapping of data sources, data movement, interfaces, and analytics, with the goal of ensuring data quality. Define standards for naming, describing, governing, managing, modeling, cleaning, enriching, transforming, moving, storing, searching, and delivering data securely. Participate in data and information model design across multiple stakeholders.

Requirements

Masters degree in Information Systems, Computer Science, Data Science or related field plus 2 years of experience in data analytics with large data sets required.
Implementation of data security standards in line with HIPAA requirements
SQL
SQL server Management Studio
Python
VBA
SSIS
Requirements Analysis
Relational databases
Business intelligence
Tableau development
ETL process development
Data management
Data engineering
Data modeling
Bachelor’s degree in Information Systems, Computer Science, Data Science or related field plus 5 years of progressive experience in data analytics with large data sets also acceptable.

Responsibilities

Develop secure, stable, scalable long-term plans for the flow of hospital data.
Assist in the development of scalable data infrastructure and platforms to collect and process large amounts of data, including structured and unstructured data for analysis by clinical, research, and business resources.
Establish methods and procedures for tracking data quality, completeness, redundancy, compliance and improvement.
Create strategies and plans for data capacity planning, data security, life cycle data management, scalability, backup and archiving.
Oversee mapping of data sources, data movement, interfaces, and analytics, with the goal of ensuring data quality.
Define standards for naming, describing, governing, managing, modeling, cleaning, enriching, transforming, moving, storing, searching, and delivering data securely.
Participate in data and information model design across multiple stakeholders.