Aws Data Engineer

Role & responsibilities:

Design, deploy, and manage cloud-native solutions using AWS services such as Glue, Lambda, S3, DynamoDB, Lake Formation, Athena, Redshift, and RDS.
Build scalable data lakes using S3 and Iceberg, ensuring secure and governed access to data for analytics and reportingImplement event-driven workflows using Lambda, SNS, and EventBridge (AWS EventHub) for automation and real-time processingDevelop APIs and integrate services to support backend systems and client applicationsMonitor, troubleshoot, and optimize infrastructure using CloudWatch and Grafana dashboardsCollaborate with cross-functional teams to define best practices, ensure security compliance, and align with business objectivesAutomate deployments using CI/CD pipelines and Infrastructure as Code (IaC) frameworksMentor junior engineers and support knowledge-sharing across teams

Preferred candidate profile:

Hands-on experience designing and implementing AWS cloud infrastructure at scale
Expertise in data lake formation, governance, and analytics using AWS Lake Formation, S3, Athena, and Iceberg Strong understanding of serverless architectures and event-driven workflows using Lambda, SNS, and EventBridge Strong knowledge of data warehousing using AWS Redshift and relational database design using Amazon RDS Proficiency in scripting languages like Python or Bash to automate cloud operations and workflows Experience developing APIs and integrating distributed systems in cloud environments Strong knowledge of DynamoDB, data modeling, and query optimization for NoSQL data stores Experience in configuring and monitoring cloud infrastructure using CloudWatch and Grafana Working knowledge of CI/CD pipelines, DevOps practices, and tools like Terraform, CloudFormation, or AWS CDK Understanding of storage formats such as Parquet, ORC, and AVRO for efficient querying and compression Familiarity with security frameworks, IAM policies, encryption, and data protection best practices Analytical mindset with strong troubleshooting and performance tuning capabilities Ability to work with structured and unstructured data in batch and streaming pipelines Demonstrated problem-solving skills, adaptability, and eagerness to learn new technologies Experience with deployment processes and containerization is a plus