Role Purpose
The Data Engineer is responsible for designing, building, and maintaining scalable
data pipelines and platforms that enable advanced analytics, operational
reporting, and data-driven decision-making.
Requirements
- 5+ years experience in data engineering, preferably in health industry
- Coding or Development Background
- Proven experience with cloud-based data ecosystems(AWS or Azure)
- Strong understanding of data modeling, ETL/ELT design, and pipeline
orchestration.
- Familiarity with regulatory data requirementsin health services.
- AWS + Databricks ( Mandatory )
- AWS Certified Data engineer (advantageous)
Duties and Responsibilities
Key Accountabilities/Kras/Kpis
- Design, develop, and maintain ETL/ELT pipelinesto collect, process, and store
structured and unstructured data from multiple systems.
- Implementstreaming and batch data workflows using cloud-native tools
- Automate ingestion from core systems
- Develop and maintain data models,storage solutions, and integrations within
cloud platforms
- Implement data lake and data warehouse architectures
- Collaborate with architectsto ensure alignment with enterprise cloud strategy
and data governance frameworks
- Optimize data storage and query performance for analytical workloads.
- Leverage partitioning, indexing, caching, and compression strategiesin cloud
data environments.
- Implement and manage monitoring and alerting for cloud infrastructure using
Datadog
- Monitor cost and performance metrics across cloud services.
- Work closely with data scientists, analysts, and software engineersto enable
advanced analytics and AI/ML use cases.
- Using DevOps practices and IaC (Infrastructure as Code).
- Participate in Agile sprint planning, backlog grooming, and technical reviews
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