Senior Application Developer - HL7FHIR Engineer

This job is responsible for designing and engineering data solutions for the enterprise and working closely with business analytic and IT stakeholders assists with the development and maintenance of these solutions. This includes coding data ingestion pipelines transformations and delivery programs/logic for people and systems to access data for operational and/or analytic needs. Duties include but are not limited to the coding testing and implementation of ingestion and extraction pipelines transformation and cleansing processes and processes that load and curate data in conformed fitforpurpose data structures. The incumbent is expected to partner with others throughout the organization (including other engineers architects analysts data scientists and nontechnical audiences) in their daily work. The incumbent will work with crossfunctional teams to deliver and maintain data products and capabilities that support and enable strategies at business unit and enterprise levels. The incumbent is expected to utilize technologies such as but not limited to: Google Cloud Platform Hadoop Hive NoSQL Kafka Spark Python Linux shell scripting SAS Teradata Oracle and Informatica.

Responsibilities

• In partnership with other business platform technology and analytic teams across the enterprise design build and maintain wellengineered data solutions in a variety of environments including traditional data warehouses Big Data solutions and cloudoriented platforms. Create high performance cloud and big data systems to be used with operational and analytic applications.
• Work with internal and external platforms and systems to connect and align on data sourcing flow structure and subject matter expertise. Work with business stakeholders and strategic partners to implement and support operational and analytic platforms. This may include products purchased by the organization that must be ingested or modeled/derived data maintained by enterprise platforms and data consumers.
• Working across multiple disparate systems and platforms design code test implement and maintain scalable and extensible frameworks that support data engineering services.
• Align with security data governance and data quality programs by driving assigned components of metadata management data quality management and the application of business rules. Develop and maintain associated data engineering processes and participate in required operating procedures as part of the enterprises overall information management activities. Includes data cleansing standardization technical metadata documentation and the deidentification and/or tokenization of data.
• Develop optimize and/or maintain machine learning and AI engineering processes (MLOps) that are deployed to cloud or big data environments. These may be based on prototypes built by data scientists or capability frameworks implemented to allow data scientists to build efficiently in production environments.
• Develop tasks across multiple projects with limited need for guidance. This includes providing guidance and education to Intermediate and Junior contributors within team. Manage relationships with customers of the function. Attend meetings with customers on a standalone basis or with team as needed.
• Establish standards and patters for high performance data ingestion transformation and delivery of data analytic needs. Keep current with Big Data technologies in order to recommend best tools in order to perform current and future work
• Other duties as assigned or requested.

Required Qualifications

• Bachelors Degree in Software Engineering Information Systems Computer Science Data Science or related field
• 5 years of experience as a developer
• 3 years of experience on HL7 standards like HL7v2 and HL7v3
• Strong knowledge on FHIR Profile implementation guide and FHIR Architecture
• Working knowledge on Google Cloud Platform (GCP) cloud technologies like BigQuery Dataflow and Pub/Sub
• Exposure to at least one FHIR based Clinical Data Repository
• Strong experience with common data engineering tools (Spark Python shell scripting)

Preferred Qualifications

• Masters Degree in Software Engineering Information Systems Computer Science Data Science or related field
• 3 years in Healthcare Industry
• 3 years of Data Warehousing
• 3 years of Database Administration