Data Integration Engineer

19 May 2024

Vacancy expired!

Job Description

Data Integration Engineer

Position Qualifications/Requirements Education:
  • Bachelor's degree in engineer, computer science, technology or another related field.
  • In lieu of degree, 15+ years of experience is required or the equivalent combination for education and experience.

Certifications/Licenses:
  • Microsoft Azure Certification(s) preferred Previous Experience
  • Professional clinical experience within clinical oncology preferred
  • 10+ years in an active healthcare big-data integration experience with multiple heterogenous data sources with data cleansing and reference/master data management on an enterprise data warehouse to create a centralized 'trusted data' set for data analysis.
  • Technical competencies (T-)SQL to create/maintain DB objects, data modeling, SSMS, SSIS, SSRS, SSAS, NoSQL, Team Foundational System (TFS), microservices, query/load required data using data governance and data visualization tools.
  • Environment competencies with on prem, data centers and Microsoft Azure cloud system tools with appropriations for disaster recovery development and production systems.
  • Florida Cancer Specialists

Job Description:

Employee Initials:
  • Domain competencies with electronic health record (EHR) (e.g. OncoEMR), practice management (e.g. Centricity), next-generation sequencing (NGS), clinical trial management (CTM), pharmacy specific to antineoplastic medications, laboratory and other healthcare ancillary systems.

Core Capabilities:
  • Data Integration Engineer has the ability to evaluate and build effective Informatics, BI, database and development teams.
  • Data Integration Engineer will work closely with the Director of Informatics and business stakeholders to build products that will create the DaaS service line and transform the BI Reporting team.
  • Being disciplined in understanding growing and contracting business needs to refactor the team and tool sets to thoughtfully set up the Informatics team for success.
  • Profound data governance knowledge of industry Best Practices.
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