Job Summary:

NOMS Healthcare is rapidly maturing its analytic and data science capabilities and is looking for an experienced healthcare engineer familiar with the Microsoft Azure Cloud-based platform. This position will develop, design, implement, and maintain a Microsoft Azure Data Warehousing environment and help architect the Enterprise Data Warehouse for all corporate entities of NOMS Healthcare. The role will include setting up and automating data pipelines via ETL / ELT processes with internal departments and external third parties, verifying data accuracy, and optimizing the data environments to enable the work of data scientists and analysts. The engineer will be expected to know SQL and Python programming and be comfortable discussing complex computer science or statistical concepts with data scientists and analysts. Innovation is critical to this role as an ideal candidate will possess the ability to lead the development of a cloud-based enterprise data warehouse, along with new reporting systems, analytic engines, and machine learning algorithms to support NOMS Healthcare.

Essential Functions:
1. In collaboration with NOMS data scientists, build full technology stack of services for commercialization purposes including PaaS (Platform as-a-service), IaaS (Infrastructure as-a-service), SaaS (software as-a-service), operations and management.
2. Manage and optimize the movement and validation of data from an Epic EMR system to NOMS Enterprise Data Warehouse.
3. Accountable for data engineering lifecycle including research, proof of concepts, architecture, design, development, test, deployment, and maintenance.
4. 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.
5. Provide guidance on synchronizing the Epic EMR data architecture with NOMS customized data models that facilitate reporting and analytics.
6. 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.
7. Build processes and diagnostic tools to troubleshoot, maintain and optimize solutions and respond to customer and production issues.
8. Provide subject matter expertise and hands on delivery of data capture, curation and consumption pipelines for Microsoft Azure.
9. Ability to build Azure data solutions and provide technical perspective on storage, big data platform services, serverless architectures, Hadoop ecosystem, vendor products, RDBMS, DW/DM, NoSQL databases and security.
10. 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.
11. Develop documentation, such as data dictionaries or guides that assists staff in identifying, locating, and using the organization’s data.

Work Experience & Education:
1. 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.
2. Minimum of 3 years of RDBMS experience.
3. Extensive hands-on experience implementing data migration and data processing using Azure services: ADLS, Azure Data Factory, Azure Functions, Synapse/DW, Azure SQL DB, Event Hub, IOT Hub, Azure Stream Analytics, Azure Analysis Service, HDInsight, Databricks Azure Data Catalog, Cosmo Db, ML Studio, AI/ML, etc.
4. Minimum of 3 years of SQL programming experience and 2 years of Python programming experience.
5. Familiarity of the environments needed to facilitate the work of data scientists and analysts in healthcare.
6. Knowledge of medical terminology, especially ICD-10 codes, CPT codes, DRG codes, and an understanding of adjudicated claims data.
7. Excellent verbal and written communication. An applicant may be asked to provide examples of written work to demonstrate technical writing proficiency.
8. Bachelors or higher degree in Computer Science, Data Science, Management Information Systems, Statistics, or any other related field.
9. Masters level work in analytics, statistics, or related field preferred.

Environmental/Working Conditions:
This job can be designed as a remote position or in-office position and preference will be discussed with applicants. This role routinely uses standard office equipment such as laptop computers and smartphones along with more advanced analytic tools such as cloud-based infrastructure. Minimal exposure to communicable diseases may be possible when collaborating in clinical settings.

Physical/Mental Demands:
Work is typically performed at a desk or table requiring the use of standard office equipment. Intermittent sitting, standing and stooping. May view computer screen for long periods of time. Work may be stressful at times.

OTHER DUTIES: This job description is not designed to cover or contain a comprehensive listing of activities, duties or responsibilities that are required of the employee for this job. Duties, responsibilities, and activities may change at any time with or without notice.