Software Data Engineer
Posted on 2/9/2024

1,001-5,000 employees

Cloud-based SaaS solutions for improved healthcare outcomes
Company Overview
Inovalon stands out as a leading healthcare technology company, leveraging its data-driven, cloud-based SaaS solutions to improve clinical outcomes and economics. Its Inovalon ONE® Platform, the most widely used cloud platform in U.S. healthcare, combines national-scale connectivity, an unparalleled primary source dataset, and advanced analytics, serving top health plans, pharmaceutical companies, and healthcare provider systems. This broad customer base, coupled with decades of healthcare and technology experience, positions Inovalon as a key player in enhancing patient care and healthcare economics.
Data & Analytics

Company Stage


Total Funding





Bowie, Maryland

Growth & Insights

6 month growth


1 year growth


2 year growth

Remote in USA
Experience Level
Desired Skills
Microsoft Azure
Development Operations (DevOps)
Data Analysis
Data & Analytics
IT & Security
  • Minimum two (2) years related experience required; healthcare industry experience preferred
  • Strong knowledge of healthcare data formats such as CMS LDS files and/or X12/EDI claims processing (specifically 837I/837P)
  • Basic understanding of Healthcare data
  • Strong working knowledge of Centers for Medicare & Medicaid Services (CMS) data
  • Basic understanding to develop SQL queries for data analysis
  • Basic understanding of Python or other programming languages
  • Basic understanding of Commercial Cloud (AWS, Azure, etc.) database tools
  • Ability to learn quickly and independently
  • Basic understanding of DevOps
  • Experience with HIPPA and PHI
  • Ability to effectively communicate with internal and external customers
  • Excellent verbal and written communication skills
  • Excellent computer proficiency (MS Office – Word, Excel and Outlook)
  • Experience working with datasets of varying complexity and form
  • Experience with test driven development methodologies
  • Bachelor’s degree in Computer Science, Software Engineering, or Information Technology
  • Take a collaborative role with the application support team to triage production problems, determine faults and provide fixes in a timely fashion, particularly with high priority items
  • Work with the software engineering team to test and validate application upgrades
  • Work with the infrastructure engineering team to test and validate system patches and production availability
  • Work with Command Center to initiate, manage, and remediate production incidents
  • Liaise with Operations, Networks and Database teams to resolve application issues
  • Update documentation to cover department level processes and procedures
  • Research customer data related questions and provide mapping between requirements and data points
  • Develop predictive and other classification methods thorough understanding of healthcare specific data sets such as CMS LDS files, 837 and 835 EDI specifications
  • Develop APIs to allow for interaction with data sets from customer facing tools
  • Perform data updates on a routine basis to keep product data sets current
  • Work and communicate in a cross-functional geographically dispersed team environment comprised of software engineers and product managers
  • Ensure compliance to company procedures when making changes and implementing code
  • Maintain compliance with Inovalon’s policies, procedures and mission statement
  • Adhere to all confidentiality and HIPAA requirements as outlined within Inovalon’s Operating Policies and Procedures in all ways and at all times with respect to any aspect of the data handled or services rendered in the undertaking of the position
  • Fulfill those responsibilities and/or duties that may be reasonably provided by Inovalon for the purpose of achieving operational and financial success of the Employer
Desired Qualifications
  • Experience with data refresh ETL, data structure development, and troubleshooting of data issues
  • Experience with data centric DevOps concepts and approaches
  • Experience with data packaging, validation, and documentation
  • Experience with Commercial Cloud (AWS, Azure, etc.) database tools
  • Experience with predictive and other classification methods
  • Experience with customer data releases