Description

You will design and implement distributed data solutions for data-intensive applications and enterprise streaming ingestion.

Responsibilities

• Implement data solutions that integrate enterprise streaming data from multiple systems for real-time ingestion and distribution.
• Develop scalable, resilient, and cost-efficient data solutions to process and utilize data across the enterprise.
• Lead complex, enterprise-wide technology initiatives and collaborate with architects, business stakeholders, and IT teams.
• Partner with Infrastructure Engineers to design systems and support data management across Development, QA, and Production environments.
• Participate in code reviews and maintain detailed technical documentation.

Required Skills

• 8-10 years of experience in data engineering.
• Expertise in AWS Aurora Postgres, DynamoDB, and MongoDB.
• Strong SQL skills and database administration for large structured and unstructured datasets.
• Proficiency in data streaming services including Kafka, Kinesis, and IBM MQ.
• Experience with Java and Spring Boot frameworks.
• Experience with workflow orchestration tools such as Airflow or Orkestration.
• Knowledge of API development using REST, GraphQL, and API Gateways.
• Experience with containerized computing using Kubernetes or AWS ECS.
• Proficiency in data formats including JSON, HL7, EDI, and XML.
• Experience with Infrastructure as Code (IaC) using CloudFormation or Terraform.
• Understanding of MDM systems like Reltio or IBM Infosphere.
• Working knowledge of Git, Jira, Agile, and DevSecOps.
• Deep technical knowledge of AWS cloud services.

Preferred Skills

• Experience in the healthcare industry focusing on clinical and billing data.
• AWS Cloud Certification.
• Familiarity with AI/MLOps and Generative AI technology.

Key Skills

Education

Bachelor's degree