Responsibilities

• Design and implement distributed data processing pipelines supporting the Nevada, and Federal Public Health ecosystems 
• Collect data from various sources, transforming and cleaning it to ensure accuracy and consistency. Load data into storage systems or data warehouses.
• Optimize data pipelines, infrastructure, and workflows for performance and scalability.
• Monitor data pipelines and systems for performance issues, errors, and anomalies, and implement solutions to address them.
• This position collaborates with Nevada’s Department of Health and Human Services and the Data Lake Governance Committee on data governance policy, data security, and data use agreements for impacted data systems required to meet the OSE mission.
• This position will collaborate with the DPBH Office of Information Technology to implement best practices and standards for systems interoperability, including HL7 v2.x and v3.x, FHIR, RESTful State APIs, public health industry data taxonomies, database connections APIs (OBDC, JDBC, ADO, etc.), and vendor-supported information systems standards.
• Lead and partner with internal and multiple solution vendors’ architecture/engineering leads and other integrated project team members to ensure high quality solutions through code reviews and software engineering best practices documentation. 
• Collaborate with Data Owners, Data Stewards, Information Technologists, Public Health Analysts, and other public health resources to identify, move, transform and curate public health data in support of Data Scientists, Epidemiologists, and Biostatisticians big data analytics and data products creation.
• Design, Develop, Modernize/Migrate pipelines to the AWS Data Lake. 
• Engage and collaborate with internal and multiple solution vendors’ DevOps by building utilities, user defined functions and frameworks to better enable data flow patterns. 
• Implement and maintain ETL processes to ensure the accuracy, completeness, consistency and security of data.
• Design and manage data storage systems, including relational databases, NoSQL databases, and data warehouses.
• Collaborate on data modeling, forecasting, and visualization projects.
• Collaborate with AWS Data Lake Project Director on data governance policies.
• Ensure compliance with Nevada security regulations and standards.
• Establish data use agreements for relevant data systems.
• Develop strategies and protocols to monitor data quality.
• Implement mechanisms to identify and rectify data errors promptly.
• Establish processes for ongoing data quality assessment and improvement.
• Knowledgeable about industry trends, best practices, and emerging technologies in data engineering, and incorporating the trends into the organization’s data infrastructure.
• Collaborate with stakeholders to develop and participate in a ‘lessons learned’ and shared knowledge cohort.
• Prepare documentation and share improvements, success stories, challenges, and opportunities throughout both State and CDC meetings/events.
• Attend training and learning opportunities addressing technical skillsets and other related information systems improvement subjects.
• Communicate effectively with partners at all levels of the organization to gather requirements, provide updates, and present findings.

Qualifications

• Required Qualifications:
• Bachelor’s degree in Computer Science, Information Technology, Data Science, or a related field.
• Minimum 5 years of relevant professional experience.
• Proficiency in programming languages commonly used in data engineering, such as Python, R, Java, Scala, or SQL. Candidate should be able to implement data automations within existing frameworks as opposed to writing one off scripts.
• Experience with big data technologies and frameworks like Hadoop, Spark, Kafka, and Flink.
• Strong understanding of database systems, including relational databases (e.g., MySQL, PostgreSQL) and NoSQL databases (e.g., MongoDB, Cassandra).
• Experience regarding engineering best practices such as source control, automated testing, continuous integration and deployment, and peer review.
• Knowledge of data warehousing concepts and tools.
• Experience with cloud computing platforms.
• Expertise in data modeling, ETL (Extract, Transform, Load) processes, and data integration techniques.
• Understanding of the underlying data models and structures used by EPIC or Cerner EHR systems, including the relational database schemas, table relationships, and data dictionaries. 
• Knowledge of common data elements, terminology standards, and coding systems (e.g., ICD-10, SNOMED CT) used to represent clinical concepts and patient information within EHR systems. 
• Experience in mapping and transforming EHR data into standardized formats for integration with other healthcare systems and analytics platforms. 
• Knowledge of the ONC United States Core Data for Interoperability (USCDI).
• Deep understanding of HIPAA, FERPA, and HITECH.  
• Familiarity with agile development methodologies, software design patterns, and best practices.
• Strong analytical thinking and problem-solving abilities.
• Excellent verbal and written communication skills, including the ability to convey technical concepts to non-technical partners effectively.
• Flexibility to adapt to evolving project requirements and priorities.
• Outstanding interpersonal and teamwork skills; and the ability to develop productive working relationships with colleagues and partners.
• Experience working in a virtual environment with remote partners and teams
• Proficiency in Microsoft Office products.


• Preferred Qualifications:
• Master’s degree in Computer Science, Health Informatics, Mathematics or related discipline.
• 3-5 years of experience in large-scale software development/Big Data technologies. 
• 3-5 years of experience in data engineering with an emphasis on data identification, data streams, data curation, data transformation, and delivery of data products. 
• 3-5 years of experience with cloud platforms and public health data solutions: Amazon Web Services (AWS), EHR, Immunization, Vital Records, Health Surveillance, etc.   
• 3-5 years of experience in SQL, data transformations, statistical analysis, and troubleshooting across more than one Database Platform (Cache’, MySQL, Snowflake, PostgreSQL, Redshift, MS SQL, etc.). 
• 3-5 years of experience developing with HL7 and FHIR HL7 interoperability standards. 
• 3-5 years of experience in the design and build of data extraction, transformation, and loading (ETL) processes by writing custom data pipelines. 
• 3-5 years of experience with one or more of the following scripting languages: Python, R, SQL, and/or others. 
• 3-5 years of experience designing and building solutions utilizing AWS Cloud services such as Lambda, Glue, Athena, API gateway, DynmoDB, etc.