Job Description
Responsibilities
∙Lead the design and implementation of scalable data architectures (data lakes, warehouses, streaming systems).
∙Build and optimize ETL/ELT pipelines for diverse data sources, ensuring high performance and reliability.
∙Drive data governance, security, and compliance initiatives across all data platforms.
∙Mentor junior engineers and provide technical guidance to cross-functional teams.
∙Collaborate with stakeholders to translate business requirements into technical solutions.
∙Implement automation and monitoring frameworks to ensure operational excellence.
∙Evaluate and adopt emerging AWS services and modern data engineering tools to enhance
capabilities.
Mandatory Skills
∙5+ years of professional experience in data engineering, with at least 4+ years working on AWS.
∙Deep expertise in AWS services: S3, Glue, Redshift, Athena, EMR, Kinesis, DynamoDB, Lambda, Step Functions.
∙Strong proficiency in SQL, Python, and Spark for data processing and pipeline development.
∙Proven experience with workflow orchestration tools (Airflow, Dagster, Step Functions).
∙Solid understanding of data modeling, partitioning strategies, and performance tuning.
∙Hands-on experience with CI/CD pipelines, Git, and Infrastructure-as-Code (Terraform/CloudFormation).
∙Familiarity with containerization (Docker, Kubernetes) and microservices-based architectures.
