Required Skills & Experience
• 6-8 years of hands-on experience in Data Engineering, ETL/ELT development, or related domains.
• Strong expertise in Apache Airflow, including DAG development, scheduling, task dependencies, monitoring, and troubleshooting.
• Proficiency in Python, React , AI,and SQL for developing and optimizing data pipelines.
• Strong understanding of ETL/ELT best practices, data validation, reconciliation, error handling, and performance optimization.
• Experience supporting production data pipelines and driving operational excellence.
• Hands-on experience with AWS services such as EKS, S3, IAM, RDS, and related cloud-native technologies.
• Hands-on experience with FastAPI for designing, developing, and maintaining RESTful APIs.
• Understanding of Kubernetes concepts, including IRSA (IAM Roles for Service Accounts), secrets management, deployments, and operational support.
• Experience with Helm charts, configuration management, and application deployment in Kubernetes environments.
• Experience with Git, CI/CD pipelines, and deployment automation tools such as Argo CD.
• Familiarity with observability and monitoring tools such as Datadog, including dashboarding, logging, alerting, and troubleshooting.
• Experience with code quality and security tools such as SonarQube, JFrog Xray, and Veracode (SAST/SCA).
• Knowledge of vulnerability remediation and secure software development practices.
• Experience working in Agile/Scrum environments with active participation in sprint ceremonies.
• Strong analytical, troubleshooting, communication, and problem-solving skills.
• Ability and willingness to quickly learn new technologies, frameworks, and business domains as needed.