Description

You will design and implement scalable data solutions for real-time ingestion, processing, and distribution across the enterprise.

Responsibilities

• Implement data solutions to integrate enterprise streaming data from multiple systems.
• Develop scalable, resilient, and cost-efficient solutions for data ingestion and processing.
• Own solution implementation end-to-end for complex, enterprise-wide technology initiatives.
• Collaborate with architects, engineers, and business stakeholders to deliver high-quality solutions.
• Ensure operational efficiency, maintain documentation, and meet SLAs through code reviews.

Required Skills

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

Preferred Skills

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

Key Skills

Education

Bachelor's degree