Data Engineer

Location: Miami, Florida, United States (Hybrid)

Industry: Hospitals and Health Care

Work Setting: HybridAre you passionate about building scalable data platforms, engineering robust data pipelines, and transforming complex data into actionable insights that support advanced analytics and decision-making? We are seeking a Data Engineer to design, develop, and maintain enterprise data solutions across on-premises and cloud environments. This role focuses on data integration, ETL/ELT development, data warehousing, cloud data management, and advanced analytics enablement while ensuring high-quality, secure, and reliable data delivery across the organization.

Data Engineering & Pipeline Development: Design, develop, and maintain scalable data pipelines that ingest, transform, and distribute data from multiple enterprise sources. Build end-to-end data integration processes supporting analytics, reporting, business intelligence, and data science initiatives. Develop data transformation frameworks that ensure consistency, quality, and usability of enterprise data assets. Support large-scale data processing across both cloud and on-premises environments. Data Integration & ETL/ELTDevelop and maintain ETL/ELT workflows that integrate data from diverse operational and analytical systems. Extract, transform, validate, and load structured and unstructured datasets from multiple sources. Ensure efficient movement and synchronization of data across enterprise platforms. Optimize data ingestion and transformation processes for performance and scalability.

Cloud Data Platforms & Data Warehousing: Support and manage cloud-based data environments such as Azure or AWS.Design and maintain data warehouse solutions that support enterprise reporting and analytics. Monitor data storage, data quality, and data distribution processes. Implement best practices for cloud data architecture, governance, and operational reliability.

Database Development & Management: Develop and optimize database schemas, tables, views, stored procedures, and data models. Write complex SQL queries to support analytics, reporting, and operational requirements. Manage and support relational and NoSQL database environments. Ensure database performance, integrity, availability, and scalability.

Analytics & Data Science Enablement: Prepare and curate data for advanced analytics, statistical modeling, machine learning, and predictive analytics initiatives. Support data scientists, analysts, and business users by delivering trusted and accessible datasets. Implement data engineering solutions that accelerate analytics development and deployment. Identify hidden patterns and trends that enable improved business insights and decision-making.

Monitoring, Quality & Governance: Monitor ETL/ELT performance and proactively resolve failures or data quality issues. Implement controls that ensure data accuracy, consistency, security, and compliance. Identify opportunities to improve data reliability, efficiency, and operational performance. Participate in data governance and quality improvement initiatives.

Collaboration & Technical Support: Collaborate with IT, analytics, research, operational, and business teams to understand data requirements. Translate business needs into scalable technical solutions. Create documentation, technical specifications, process flows, and data models. Support ongoing platform enhancements, upgrades, and optimization initiatives.

Preferred Qualifications: Experience working with healthcare technology, clinical systems, or research data environments. Familiarity with enterprise healthcare systems and electronic health records (EHRs).Experience with healthcare interoperability standards including HL7 and FHIR.Experience supporting large-scale enterprise data warehouse environments. Knowledge of data governance, master data management, and data quality best practices. Experience working with both relational and NoSQL databases.