Minimum of 8-10 years of experience in data engineering.
Expertise in cloud databases such as AWS Aurora Postgres, DynamoDB, MongoDB for efficient data processing, ingestion & distribution.
Expertise in optimizing database performance through sharding, partitioning, indexing, query optimization, and other tuning techniques.
Expertise in cloud-based data storage solutions like Amazon S3 or Google Cloud Storage.
Expert SQL and database admin skills working with large structured and unstructured data.
Experience in workflow orchestration tools like Airflow Orkes etc.,
Proficiency in data streaming services such as Kafka, Kinesis, and IBM MQ Expertise in developing programs to produce and read payloads from data streaming solutions like Kafka, Kinesis Data Streams.
Experience in java programming language including frameworks like Spring Boot etc.,
Experience with API development (REST, GraphQL), API Gateways etc.,
Strong understanding of scalable containerized computing and solutions for example Kubernetes, AWS ECS etc.,
Proficiency in data formats such as JSON, HL7, EDI, and XML
Good understanding of MDM systems/concepts and tools like Reltio, IBM Infosphere etc., System development lifecycle (SDLC), Agile Development, DevSecOps, and standard software development tools such as Git and Jira Infrastructure as Code (IaC) technologies such as CloudFormation or Terraform Familiarity with AI/MLOps concepts and Generative AI technology (Good to have)
Deep technical knowledge of 1 public cloud services (preferably AWS)
Excellent problem-solving and analytical skills
Strong communication and collaboration skills with both technical and non-technical stakeholders.
Preferred Qualifications: Experience in the healthcare industry, preferably focusing