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About the Role

Integrates, builds, and maintains data pipelines and data transformation algorithms for enterprise data analytics consumption. Responsible for data integration, monitoring of data storage, and data distribution across multiple on premise and cloud-based data environments in preparation for sophisticated analytics consumption, data mining, and enterprise data insights.

Responsibilities

• Designs and develops highly scalable, end-to-end processes to consume, integrate, and analyze large volumes of complex data from dispersed data sources on both on-premise and cloud-based environments.
• Integrates, builds, and maintains data pipelines and data transformation algorithms for enterprise data analytics consumption.
• Manages data integration, monitors data storage, and oversees data distribution across multiple on-premise and cloud-based environments for analytics, data mining, and insights.
• Communicates effectively with IT, research, and medical staff.
• Integrates and ETL/ELT datasets and flows using various open-source and proprietary software.
• Writes complex, efficient queries against large, disparate data sources.
• Monitors ETL/ELT performance and ensures compliance with security standards.
• Deploys sophisticated analytics programs, machine learning, and statistical methods.
• Prepares data for predictive and prescriptive modeling.
• Identifies hidden patterns in data to improve business insights.
• Utilizes machine learning patterns for data discovery and automation tasks.

Requirements

• Bachelor's Degree in IT, Biomedical Informatics, Computer Science, Engineering or related field with at least 4 years of combined experience in Clinical IT and/or Research, OR Master’s degree in IT, Biomedical Informatics, Computer Science, Engineering with at least 2 years of combined experience in Clinical IT and/or Research.
• 1-3 years of data engineering and integration experience.
• 1-3 years of data management in cloud-based data environments such as Azure or AWS.
• 3-5 years of experience developing database schemas, querying, managing, or curating Oracle PL/SQL or SQL server databases.
• 1-3 years of data warehousing ELT/ETL experience.
• 1-3 years of experience with Python, SQL, SSIS, or Informatica for data ETL and data transformations.
• Experience working with APIs/RESTful Web Services.
• Experience with XML, JSON, HL7, or FHIR.
• Experience with data visualization tools such as Tableau or Power BI.
• Direct experience or strong familiarity with commercial EHR platform and/or PeopleSoft.
• Experience extracting and managing data from large enterprise clinical and non-clinical systems.
• Familiarity with and experience with efficient database ETL processes – extracting data from a wide range of data sources, normalizing data, creating and providing entity relationship diagrams, schemas and related documentation, creating primary and foreign keys and indexing, writing functional and technical specifications.
• Ability to learn and apply new technical skills.
• Willingness and ability to share knowledge with other team members.
• Ability to adapt to changes in a fast-paced healthcare and data environment.
• Identify ways to improve data reliability, efficiency, and quality.
• Effective work experience developing, integrating, and supporting data systems; working with a combination of both relational and NoSQL databases.

Skills

• Python
• SQL
• SSIS
• Informatica
• APIs
• RESTful Web Services
• XML
• JSON
• HL7
• FHIR
• Tableau
• Power BI
• Oracle PL/SQL
• SQL Server
• NoSQL databases
• Machine learning
• Statistical methods

Experience Level

• 4 years of combined experience in Clinical IT and/or Research (if Bachelor's)
• 2 years of combined experience in Clinical IT and/or Research (if Master's)
• 1-3 years of data engineering and integration experience
• 1-3 years of data management in cloud-based data environments
• 3-5 years of experience developing database schemas, querying, managing, or curating Oracle PL/SQL or SQL server databases
• 1-3 years of data warehousing ELT/ETL experience
• 1-3 years of experience with Python, SQL, SSIS, or Informatica for data ETL and data transformations

Education Level

• Bachelor's Degree in IT, Biomedical Informatics, Computer Science, Engineering or related field
• Master’s degree in IT, Biomedical Informatics, Computer Science, Engineering