We are looking for a passionate Data Engineer who can help to turn data into insights. This position will be responsible for building and maintaining scalable data infrastructure ranging from Data Ingestion Pipelines, Data Modeling and Data integration to support analytics and self-service data exploration. Work closely with leaders across the organization to understand their data needs and empower them to make critical decisions backed by data.
- Understanding of Hospital Revenue Cycle operational workflows
- Perform in-depth analysis of Patient Financial Services workflows and designs and implement data infrastructure to be used at an enterprise level. For example, Hospital Revenue Cycle such as claims, charges, insurance follow ups, denials, appeals payors/plans, bad debt etc.
- Understand and analyze business operations as they relate to software design and build decisions to implement data solutions.
- Drive optimization by providing data engineering solutions in terms of building data ingestion pipelines and curated/enriched data sets.
- Analyze new functionalities released by EPIC (EMR vendor) as part of their revenue Cycle module and determine how the datasets should be leveraged.
- Partner with data analysts, product managers, engineers, and business stakeholders to obtain a holistic understanding of each team’s data needs and translate into infrastructure and tooling that enables a data-driven culture.
- Own data integrity, availability, transformation logic, and efficient data access to support the growing needs of the organization.
- Identify opportunities for improvements and automation opportunities to drive DataOps service.
- Work independently and effectively manages time across multiple priorities and projects.
- Understand and document how data is, or will be used, and its implications on people, processes, products and technology.
- Implement appropriate data modelling governance framework.
- Ability to gather information from multiple sources and analyze applicability and appropriateness, and develop efficient workflows.
- Experience with organizational strategies, business operations, and end-user requirements to develop data infrastructure.
- Reporting – collaborate with colleagues across the enterprise to scope requests. Extract data from various data sources, validate results, create relevant data visualizations, and share with requester. Develop dashboards and automate refreshes as appropriate.
- Develop analytics tools that utilize data resources to provide actionable insights, operational efficiency and other key business performance metrics.
- Proficient at integrating predictive and prescriptive models into applications and processes.
- Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement.
- A successful history of manipulating, processing and extracting value from large disconnected datasets.
- Working knowledge of message queuing, stream processing, and highly scalable data stores.
- Make recommendations about platform adoption, including technology integrations, application servers, libraries, and frameworks.
- Participate in a shared production on-call support model.
- Be a critical part of a scrum team in an agile environment, ensuring the team successfully meets its deliverables each sprint
- Serve as a mentor for all Data Engineers.
- Must possess critical thinking and creative problem solving skills along with the ability to communicate well with stakeholders throughout the organization
Job Responsibilities (Continued)
Job Responsibilities (Continued)
Required Licenses, Certifications, Registrations
Two (2) Certifications or proficiency in appropriate Data Science/Data Integration/Data Warehousing technology or subject domain.
Required Education and Experience
Required Education: Bachelor’s Degree in Computer Science, Computer/Software Engineering, Information Technology or related fields.
Required Experience: 8+ years of Data Engineering/Business Intelligence/Data Warehousing experience, preferably in a healthcare environment.
Preferred Education, Experience & Cert/Lic
- Advanced Degree in Computer Science, Informatics, Information Systems or another quantitative field.
- Minimum of ten (10) years of experience in a Data Engineer role
Additional Technical Requirements
- Highly proficient in SQL
- Experience with big data tools: Hadoop, Spark, Kafka, BigSQL, Hive, sqoop etc.
- Experience with relational SQL and NoSQL databases, including IBM PDA (Netezza), MS SQL Server and HBase.
- Experience with data integration tools: DBT, Informatica, MS Integration Services etc.
- Experience with cloud vendors and services: AWS, GCP, Azure
- Experience with stream-processing systems: IBM Streams, Flume, Storm, Spark-Streaming, etc.
- Experience consuming and building APIs
- Experience with object-oriented/object function programming languages: Python, Java, C++, Scala, etc.
- Experience with statistical data analysis tools: R, SAS, SPSS, etc.
- Experience with visual analytics tools: QlikView, Tableau, Power BI etc.
- Experience utilizing Agile methodology for development
- Experience with electronic health record and financial systems. i.e. Epic Systems, Cerner, WorkDay, Infor, Strata etc.