Senior Full-Stack AWS Data Engineer

Job Title:
Senior Full-Stack AWS Data Engineer

Duration:
Long-Term

Job Summary:

We are seeking an experienced Senior Full-Stack AWS Data Engineer to design, develop, and maintain scalable cloud-based data platforms and modern data pipelines. The ideal candidate will have strong expertise in Python, PySpark, SQL, AWS services, data lake architecture, and ETL/ELT development, along with experience in infrastructure automation, streaming data integration, and production support.

Key Responsibilities:

• Design, develop, and optimize scalable ETL/ELT pipelines using Python, PySpark, and SQL.
• Build and maintain cloud-based data solutions using AWS S3, Glue, IAM, Kinesis, ECS, and EKS.
• Implement and optimize data warehouses and query solutions using Snowflake, Amazon Redshift, and Athena.
• Design streaming and real-time data integration solutions using Amazon Kinesis and Confluent.
• Build and manage modern data lakes using Apache Iceberg and related technologies.
• Automate cloud infrastructure provisioning using Terraform and Infrastructure as Code (IaC) practices.
• Implement CI/CD pipelines using Git Lab, Git Hub, and Dev Ops tools.
• Manage containerized workloads and support scalable deployments using Docker and Kubernetes.
• Monitor data pipeline performance, troubleshoot production issues, and implement observability solutions.
• Apply Data Ops and Dev Ops practices to improve data quality, reliability, security, and deployment efficiency.
• Collaborate with data architects, analysts, and engineering teams to deliver reliable enterprise data solutions.

Required Qualifications:

• Strong experience in data engineering and scalable data architecture.
• Advanced proficiency in Python, PySpark, and SQL.
• Hands-on experience with AWS cloud services, including S3, Glue, IAM, and Kinesis.
• Experience building and maintaining scalable ETL/ELT data pipelines.
• Knowledge of ECS/EKS, containerized workloads, and Kubernetes.
• Experience with Terraform and infrastructure automation.
• Hands-on experience with dbt Core and modern data transformation practices.
• Experience with Snowflake, Redshift, and Athena.
• Knowledge of streaming data platforms such as Kinesis and Confluent.
• Experience with Git Lab/Git Hub, CI/CD pipelines, and version control.
• Understanding of Apache Iceberg and modern data lake architectures.
• Strong knowledge of Data Ops, Dev Ops, monitoring, and production troubleshooting.

Preferred Qualifications:

• Knowledge of data governance, data quality, and security best practices.
• Experience with automated data testing and pipeline orchestration.
• Strong analytical, problem-solving, and communication skills.