Data Engineer (Infrastructure & Operations)
Obligāti:PythonAWSAzureGoogle CloudCloudDataAI
- Design and build a centralized data lake with governance standards, data ingestion patterns, and AI/ML-ready architecture
- Integrate data across core enterprise and clinical systems — HIS, ERP, RCM, LIS/RIS, and other operational platforms — normalizing disparate schemas into a unified model
- Manage and optimize production databases — primarily Oracle (relational), plus NoSQL where used — including access controls, backups, and performance tuning
- Plan and execute end-to-end data migrations from legacy systems into the unified platform
- Design system integrations and build/maintain ETL/ELT pipelines across environments
- Write production-grade scripts (Python, SQL, Bash) for automation, monitoring, and transformation
- Design data models powering business reports and analytics; maintain dashboards and BI pipelines
- Serve as second-line escalation for data infrastructure incidents
- Bachelor’s in CS, Data Engineering, or equivalent experience
- 6+ years in data engineering, database administration, or related infrastructure roles
- Strong SQL and Python; Bash/Shell scripting
- Strong Oracle Database experience — PL/SQL, query and performance tuning, and working with Oracle as a primary transactional and source system
- Hands-on experience building data lake / lakehouse architectures on at least one major cloud platform (AWS, OCI, Azure, or GCP) — object storage, catalog, and query layers, with transferable understanding across providers
- Understanding of data governance, ETL/ELT pipelines, and system integration patterns
- Working knowledge of cloud data governance, access control, and encryption in a regulated-data environment
- Familiarity with monitoring and observability tools