Jobs → Data & Analytics → Senior Data Engineer

Senior Data Engineer

Athif Mohammed - CSMUnited StatesSENIORPosted 2h ago
AWSPythonApplication IntegrationAWS GlueLambdaEKSS3DynamoDBDocumentDBKafkaTerraformJenkinsGitSQLNoSQLRESTful APIsEvent-Driven ArchitectureCI/CDDistributed SystemsCloud-Native Development
About the Role We are looking for a highly experienced Senior Data Engineer with strong hands-on expertise in AWS, Python Application Development, Integration Patterns, and Cloud Infrastructure for an insurance client. Key Responsibilities • Design and develop scalable Python applications, RESTful APIs, and AWS-based data engineering solutions • Build application integrations using REST APIs, event-driven, file-based, and batch-processing patterns • Develop distributed applications using AWS Glue, Lambda, EKS, S3, DynamoDB, and DocumentDB • Implement Kafka-based event-driven integrations with a strong understanding of event processing patterns • Manage AWS infrastructure, security, IAM, DNS, and Route 53 • Provision and manage cloud resources using Terraform (IaC) • Build and maintain CI/CD pipelines using Jenkins and Git • Create production-ready Low-Level Designs (LLD) and optimize SQL/NoSQL databases • Lead technical discussions, mentor developers, and conduct code reviews Requirements • 13–15 years of experience (mandatory) • Advanced programming, application development, and software design patterns in Python • Strong expertise in AWS services: Glue, Lambda, EKS, S3, DynamoDB, DocumentDB, EC2, IAM, Route 53 • Experience with integration patterns: RESTful APIs, Event-Driven Architecture, Kafka, File-Based and Batch Integrations • Infrastructure & DevOps skills: Terraform, Jenkins, Git, CI/CD • Database expertise: SQL, NoSQL, Schema Design, Query Optimization • Architecture knowledge: Distributed Systems, Application Integration, LLD, and Cloud-Native Development Important Hiring Manager Expectations We are specifically looking for candidates with strong application development and application integration experience within Data Engineering, not just traditional ETL or data pipeline development. Candidates must have a deep understanding of REST-based, event-driven, file-based, and batch integration patterns. Experience using Kafka alone is not sufficient without a strong understanding of event-driven integration architecture.

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