- Design, develop, and maintain ETL processes to support data ingestion, transformation, and loading into the data warehouse.
- Work with AWS cloud services and EKS to deploy and manage scalable data workloads.
- Implement container-based deployments using Docker and EKS for ETL applications.
- Write and maintain scripts in Python and Unix for automation and data pipeline orchestration.
- Monitor, troubleshoot, and optimize data pipelines for performance and reliability.
- Collaborate with data analysts, data scientists, and business teams to deliver accurate, timely, and high-quality data.
- Ensure adherence to best practices for data governance, security, and compliance.
Years of Experience:4 7 years of experience in data engineering or data warehouse development with hands-on experience in ETL frameworks and cloud technologies.
- Educational Qualification & Certifications (Optional):Bachelor s degree in Computer Science,
Information Systems, or related field.
- AWS certifications (e.g., AWS Certified Data Analytics Specialty, AWS Certified Developer) are a plus.
Skill Set Required:
Must Have:
- Strong knowledge of ETL frameworks and data pipeline development.
- Hands-on experience with AWS cloud services and EKS.
- Experience deploying applications in containers (Docker, EKS).
- Solid proficiency in Unix scripting and Python programming.
Nice to Have:
- Experience with data modeling, data warehousing concepts (e.g., star schema, snowflake schema).
- Familiarity with orchestration tools like Airflow, Step Functions, or Glue.
- Knowledge of CI/CD practices for data pipeline deployments.
- Exposure to data security and compliance requirements.