AWS Data & Integration Engineer

SUMMARY

📍Remote or hybrid (Kraków)

⏱ Project: 3 months

PROJECT

You will join a project focused on modernizing an existing ODS (Operational Data Store) platform, where current batch-based and Heroku-based integrations are being migrated to an AWS-native, near-real-time, event-driven architecture.

The goal of the project is to build a scalable and reliable integration layer supporting multiple data sources and downstream systems.

YOU WILL

• Design and develop integration solutions based on AWS and event-driven architecture
• Build APIs and data flows using REST/JSON
• Work with EventBridge, SQS, SNS, Lambda, API Gateway, S3 and CloudWatch
• Implement data contracts, schema validation, versioning, and data transformations
• Build mechanisms for retry, DLQ, idempotency, error handling, and replay
• Integrate data from systems such as Oracle, SQL Server, PostgreSQL, Salesforce, and ServiceNow
• Support migration of existing integrations from ODI, MuleSoft, and Heroku to AWS
• Develop unit and integration tests and support performance testing
• Participate in deployments, production cutovers, troubleshooting, and post-production support
• Collaborate with the Principal Architect and other teams to define reusable enterprise integration patterns

MUST HAVE

• 6+ years of experience in software/data integration engineering
• Strong hands-on experience with AWS
• Development experience in Python
• Strong knowledge of REST APIs, JSON, SQL, and event-driven architecture
• Experience with several AWS services, including: EventBridge, SQS / SNS, Lambda, API Gateway, S3, CloudWatch, IAM / KMS
• Experience with relational databases and enterprise data integration
• Knowledge of CI/CD and Git
• Strong analytical and troubleshooting skills

NICE TO HAVE

• Kafka / Amazon MSK
• Terraform / CloudFormation
• DynamoDB / DocumentDB
• Redshift
• Data Lake architecture
• CDC technologies
• ODI, MuleSoft, or Heroku experience
• Experience modernizing legacy integration platforms to AWS
• Experience with high-volume or near-real-time processing
• Understanding of reliability, scalability, security, and production readiness principles