Data warehouse professionals

Roles & Responsibilities:

• 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).
• Strong 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.