ETL Data Engineer

Overview

Position:
Data Engineer / ETL Data Engineer in Lansing, MI, US. The role is responsible for providing ongoing maintenance and support of the Michigan Disease Surveillance System (MDSS). MDSS supports communicable disease surveillance, registries, and case management systems critical to public health responses. The system is undergoing modernization to enhance stability and functionality. The resource is integral to developing, maintaining, and enhancing MDSS phase 1, ensuring automated processes function, streamlining critical business processes, data integrity, SEM/SUITE compliance, and security.

The resource also acts as a technical lead, providing guidance to other developers and participating in analytical assignments for enhancement, integration, maintenance, and implementation of projects. By providing technical oversight to the team, this role helps prevent outages and data integrity issues that could affect patient information reporting.

• Lead the design and development of scalable and high-performance solutions using AWS services.
• Experience with Databricks, Elastic Search, Kibana, S3.
• Experience with Extract, Transform, and Load (ETL) processes and data pipelines.
• Write clean, maintainable, and efficient code in Python/Scala.
• Experience with AWS Cloud-based application development.
• Experience in Electronic Health Records (EHR) HL7 solutions.
• Implement and manage Elastic Search engine for efficient data retrieval and analysis.
• Experience with data warehousing and data visualization tools; ensure data integrity.
• Execute full software development life cycle (SDLC) including requirements gathering and writing functional/technical specifications for complex projects.
• Design both logical and physical database models; develop database objects including stored procedures and functions.
• Extensive knowledge of source control tools such as Git.
• Develop software design documents and collaborate with stakeholders for review and approval.
• Document system requirements with flowcharts and screen layouts to ensure logical flow.
• Experience working on large agile projects and creating CI/CD pipelines (preferably using Azure Dev Ops).

• 12+ years developing complex database systems.
• 8+ years with Databricks.
• 8+ years using Elastic Search and Kibana.
• 8+ years using Python/Scala.
• 8+ years with Oracle.
• 5+ years experience with ETL processes and developing data pipelines.
• 5+ years experience with AWS.
• 5+ years experience with data warehousing, data visualization tools, and data integrity.
• 5+ years experience with CMM/CMMI Level 3 methods and practices.
• 5+ years experience with agile development processes including test-driven development.
• Experience or knowledge in creating CI/CD pipelines using Azure Dev Ops is a plus.