Data Engineer

Job Summary 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. Job Responsibilities Design and develop highly scalable, end-to-end processes to consume, integrate, and analyze large volume, complex data from dispersed data sources on both on premise and cloud-based data environments and systems. Integrate, build, and maintain data pipelines and data transformation algorithms for enterprise data analytics consumption. Monitor data integration, storage, and distribution across multiple on premise and cloud-based data environments in preparation for sophisticated analytics, data mining, and enterprise data insights. Engage and communicate effectively with a variety of IT, research, and medical staff. Integrate and ETL/ELT datasets and flows using a variety of open source and best-in-class proprietary software. Write complex, efficient queries against large and disparate data sources. Monitor ETL/ELT performance and ensure compliance with security. Deploy sophisticated analytics programs, machine learning, and statistical methods. Prepare data for predictive and prescriptive modeling. Find hidden patterns using data to improve business insights. Use machine learning patterns for data discovery and tasks that can be automated. Qualifications 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 the use of Python, SQL, SSIS, or Informatica for data ETL and data transformations. Experience working with API’s/RESTful Web Services. Experience with XML, JSON, HL7, or FHIR. Experience with data visualization tools such as Tableau or Power BI. Knowledge, Skills, and Abilities Direct experience or strong familiarity with commercial EHR platforms and/or PeopleSoft. Experience extracting and managing data from large enterprise clinical and non-clinical systems. Familiarity with efficient database ETL processes – extracting data from a wide range of sources, normalizing data, creating 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 both relational and NoSQL databases. #J-18808-Ljbffr