Senior Data Engineer (Onsite or Remote)

Data Engineer

Experience with AWS infrastructure including AWS Connect and AWS Lambda.

Manage and optimize the movement and validation of data from an Epic EMR system to SQL databases in AWS or Azure and either from or to the Salesforce platform.

Accountable for data engineering lifecycle including research, proof of concepts, architecture, design, development, test, deployment, and maintenance. This role will focus on AWS optimization with some work occurring in other cloud-based environments.

Oversee the development of novel data pipelines that integrate and normalize large data from a variety of sources (e.g., electronic health record, claims, wearable device, publicly available data, etc.) to enable learning health, machine learning model development, and deployment.

Design, direct and implement ETL processes, including data capture, data quality, testing and validation methods.

Layer in instrumentation in the development process so that data pipelines can be monitored. Measurements are used to detect internal problems before they result into user visible outages or data quality issues.

Build processes and diagnostic tools to troubleshoot, maintain and optimize engineering environments and respond to production issues.

Provide subject matter expertise and hands on delivery of data capture, curation, and consumption pipelines for AWS.

Participate in deep architectural discussions to build confidence and ensure customer success when building new solutions and migrating existing data applications on the Azure platform.

Develop documentation, such as data dictionaries, guides, or data flow diagrams that assists staff in identifying, locating, and using the organizations data.

Qualifications:

Incumbent Must Possess:

Minimum of 3 years of SQL programming experience and associated SQL tools (SSIS, SSMS, SSRS, etc.).

Experience with Visual Studio is preferred.

At least 3 years of experience in developing data ingestion, data processing and analytical pipelines for big data, relational databases, NoSQL and data warehouse solutions.

Minimum of 3 years of RDBMS experience.

Extensive hands-on experience implementing data migration and data processing using Amazon Web Services. Includes knowledge of Amazon Connect and Amazon Lambda.

Knowledge of medical terminology, especially ICD-10 codes, CPT codes, DRG codes, and an understanding of adjudicated claims data.

Excellent verbal and written communication. An applicant may be asked to provide examples of written work to demonstrate technical writing proficiency.

Education: Masters degree with 10 years experience preferred; Bachelors degree with 13 years of equivalent experience will be considered in place of masters degree requirement. Experience: Requires a minimum of 10 years experience with at least five (5) years working in data management, data engineering, or data architecture. Enterprise Data Warehouse development preferred; Requires at least five (5) years working with healthcare data; more is preferred. SQL proficiency is required.

License(s): None

Certification(s): Certification work related to Epic or Amazon Cloud may be required within 1 year of starting employment.