Role Description CTG is seeking a highly skilled Healthcare Data Engineer to support enterprise healthcare data initiatives. This role will focus on designing and building scalable cloud-based data pipelines, integrating large healthcare datasets, and enabling advanced analytics using modern data engineering technologies. The ideal candidate will have strong experience with cloud platforms, big data processing frameworks, and healthcare data environments. Location: Remote Duration: 6 Months Key Responsibilities - Design, develop, and optimize enterprise-scale ETL/ELT pipelines. - Build and maintain cloud-native data solutions using AWS and/or GCP. - Develop data processing applications using Python, PySpark, and Scala. - Integrate and transform data across Teradata, Snowflake, and other enterprise systems. - Implement scalable data architectures supporting healthcare analytics and reporting. - Deploy and manage containerized data workloads using Kubernetes. - Ensure data quality, governance, security, and compliance with healthcare regulations. - Collaborate with architects, analysts, and business stakeholders to deliver data-driven solutions. - Troubleshoot and optimize performance of large-scale data platforms. Qualifications - Strong experience with AWS and/or Google Cloud Platform (GCP). - Advanced ETL/ELT development expertise. - Hands-on experience with Teradata and Snowflake. - Strong programming skills in Python, PySpark, and Scala. - Unix/Linux administration and scripting experience. - Experience working with Kubernetes and containerized environments. - Understanding of healthcare data ecosystems and industry regulations. - Strong analytical, problem-solving, and communication skills. Requirements - 7+ years of Data Engineering experience. - Experience supporting healthcare organizations, payers, providers, or health technology companies. - Familiarity with claims, clinical, member, provider, or population health data. - Experience building large-scale cloud data platforms and distributed data processing solutions. - Knowledge of HIPAA compliance and healthcare data governance practices. Education - Bachelor's degree in Computer Science, Information Systems, Data Engineering, Healthcare Informatics, or a related field. - Advanced degree and relevant cloud certifications are a plus. - Excellent verbal and written English communication skills and the ability to interact professionally with a diverse group are required. Benefits - The expected base salary for this position ranges from $185,000 to $195,000. - Salary offers are based on a wide range of factors including relevant skills, training, experience, education, market factors, and where applicable, licensure or certifications obtained. - In addition to salary, a competitive benefit package is also offered. To Apply To be considered, please apply directly to this requisition using the link provided. Kindly forward this to any other interested parties. Thank you!

• Own our canonical data architecture — the schema, contracts, tenancy, and governance. • Make production data AI-ready: well-modeled, contract-enforced, lineage-tracked, and drift-detectable. • Own the canonical data model — the normalized definition of the core business objects shared across our products. • Define the multi-tenant data architecture: tenancy isolation, data residency posture, and per-tenant cost attribution. • Lead staged modernization toward the right mix of stores and patterns. • Own the architectural direction of the data pipeline and lake / lakehouse layer. • Drive hands-on prototypes, reference implementations, and in-repo guardrails. • Partner with database engineering on production data health while owning long-term architectural direction.

• Define and document end-to-end data architectures, from source ingestion to analytical consumption layers, ensuring scalability, performance, and governance • Establish technical standards, development guidelines, and architectural decisions to promote consistency across projects and teams • Lead adoption and evolution of Lakehouse architecture (Medallion Architecture) in Databricks and Azure environments, including partitioning, clustering, and Delta Table optimization strategies • Define and guide data ingestion strategies for batch, incremental, CDC, and streaming scenarios • Provide technical leadership for data modeling decisions appropriate to the analytical context and consumption patterns • Ensure implementation of data governance practices (cataloging, lineage, access control at object/row/column levels) • Act in a consultative capacity with clients, conducting technical discovery, gathering requirements, and presenting architectural proposals • Support and review the work of data engineers, ensuring adherence to defined standards and promoting development best practices • Collaborate with BI, Engineering, and AI teams to define the data layers that support analytical, semantic, and ML models • Evaluate and recommend technologies, tools, and integration patterns aligned with the Azure + Databricks ecosystem • Monitor the health of data platforms (quality, SLAs, compute and storage costs) and propose continuous improvements • Contribute to pre-sales activities and technical qualification of opportunities by developing reference architectures and effort estimates.

• Participar en la definición y ejecución de estrategias de migración de datos. • Realizar análisis de estructuras origen y destino. • Implementar, administrar y validar estructuras de bases de datos. • Garantizar la integridad, consistencia y calidad de los datos migrados. • Ejecutar procesos de validación y conciliación de información. • Participar en pruebas funcionales, de carga y rendimiento. • Gestionar incidencias relacionadas con bases de datos durante la ejecución del proyecto. • Elaborar documentación técnica y evidencias de migración. • Apoyar la definición y ejecución de estrategias de gestión de datos históricos. • Analizar y definir proceso de integraciones con sistemas satélite y terceros.