Proficiency in Python, SQL, and Spark for data processing and transformation.
Hands-on experience with AWS Glue, Redshift, Athena, EMR, S3, and Lambda.
Experience with ETL orchestration tools (Step Functions, Airflow, Prefect, Dagster).
Familiarity with containerization (Docker, Kubernetes, ECS) and CI/CD pipelines.
Understanding of data security, IAM policies, and encryption best practices.
Nice to have:
AWS certifications such as AWS Certified Data Analytics – Specialty or AWS Certified Solutions Architect.
Experience with Machine Learning and AI/ML data pipelines in AWS.
Knowledge of serverless data engineering with Lambda and API Gateway.
Hands-on experience with NoSQL databases (DynamoDB, MongoDB, OpenSearch).