Principal Engineer – Data
Aspirion Health Resources LLC
- Atlanta, GA
- Permanent
- Full-time
- Architect and implement scalable data management solutions, integrating modern and traditional database technologies.
- Lead the design and optimization of NoSQL, Graph DB, and relational databases to support business analytics and operational needs.
- Develop and oversee Data Lake, Data Warehouse, and Data Lakehouse solutions, ensuring best practices for data storage and retrieval.
- Ensure HIPAA and HiTrust compliance, implementing security best practices such as encryption, access controls, and audit logging.
- Design and implement data integration pipelines, leveraging ETL and EDI standards to ensure smooth data exchange.
- Provide architectural guidance on AI/ML data requirements, ensuring data models support advanced analytics and machine learning workloads.
- Collaborate with cross-functional teams to align data architecture with business goals and drive enterprise data strategy.
- Define best practices for data governance, data quality, and metadata management to improve reliability and accuracy.
- Evaluate and recommend modern data technologies to enhance system performance, scalability, and maintainability.
- Mentor and guide data engineers and developers in implementing best-in-class data architectures.
- Bachelor’s or Master’s degree in Computer Science, Data Science, Software Engineering, or a related technical field.
- Minimal 10 years of experience in data architecture and engineering, with expertise in modern data technologies.
- Proven track record of designing and implementing large-scale data solutions in an enterprise environment.
- Expertise in database technologies: NoSQL (MongoDB, Cassandra, Cosmos DB), Graph DB (Neo4j, AWS Neptune), and relational databases (SQL Server, Azure SQL, MySQL on AWS).
- Experience with enterprise data architecture: Data Lakes, Data Warehouses, and Lakehouse implementations.
- Strong understanding of healthcare data and security standards: HIPAA, HiTrust, and best practices for data security and compliance.
- Proficiency in EDI and ETL tools, ensuring efficient data integration and processing.
- Experience with AI/ML data preparation, designing architectures that support analytics and machine learning models.
- Cloud expertise: Hands-on experience with Azure, AWS, or Google Cloud for data solutions.
- Strong analytical and problem-solving skills, with the ability to troubleshoot data challenges.
- Excellent communication and collaboration skills, working effectively across teams.