Data Engineering Manager

Job Description

Description - Internal 'Accountable for the data engineering lifecycle including research, proof of concepts, architecture, design, development, test, deployment, and maintenance. Design, develop, implement, and run cross-domain, modular, flexible, scalable, secure, reliable, and quality data solutions that transform data for meaningful analyses and analytics while ensuring operability. Layer in instrumentation in the development process so that data pipelines that can be monitored to detect internal problems before they result in user-visible outages or data quality issues. Build processes and diagnostic tools to troubleshoot, maintain, and optimize solutions and respond to customer and production issues. Embrace continuous learning of engineering practices to ensure industry best practices and technology adoption, including DevOps, Cloud, and Agile thinking. Tech debt reduction/Tech transformation including open source adoption, cloud adoption, HCP assessment, and adoption. Maintain high-quality documentation of data definitions, transformations, and processes to ensure data governance and security' Functions may include database architecture, engineering, design, optimization, security, and administration; as well as data modeling, big data development, Extract, Transform, and Load (ETL) development, storage engineering, data warehousing, data provisioning and other similar roles. Responsibilities may include Platform-as-a-Service and Cloud solution with a focus on data stores and associated eco systems. Duties may include management of design services, providing sizing and configuration assistance, ensuring strict data quality, and performing needs assessments. Analyzes current business practices, processes and procedures as well as identifying future business opportunities for leveraging data storage and retrieval system capabilities. Manages relationships with software and hardware vendors to understand the potential architectural impact of different vendor strategies and data acquisition. May design schemas, write SQL or other data markup scripting and helps to support development of Analytics and Applications that build on top of data. Selects, develops and evaluates personnel to ensure the efficient operation of the function. - Generally work is self-directed and not prescribed. - Works with less structured, more complex issues. - Serves as a resource to others. Qualifications - Internal - Undergraduate degree or equivalent experience. 'Proficient in design and documentation of data exchanges across various channels including APIs, streams, batch feeds Proficient in source to target mapping, gap analysis and applies data transformation rules based on understanding of business rules, data structures Develops and implements scripts to maintain and monitor performance tuning. Designs scalable job scheduler solutions and advises on appropriate tools/technologies to use. Works across multiple domains to define and build data models Understands all the connected technology services and their impacts. Assesses design and proposes options to ensure the solution meets business needs in terms of security, scalability, reliability, and feasibility. ' 'Understanding of healthcare data, including Electronic Health Records (EHR), claims data, and regulatory compliance such as HIPAA. Familiarity with healthcare regulations and data exchange standards (e.g. HL7, FHIR) Experience with data analytics tools like Tableau, Power BI, or similar. Familiarity with automation tools and scripting languages (e.g., Bash, PowerShell) to automate repetitive tasks. Experience in optimizing data processing workflows for performance and cost-efficiency.'