Description

Design, build, and manage scalable ETL/ELT data pipelines for efficient data ingestion and transformation.

This role is on-site.

Responsibilities

• Design and build scalable ETL/ELT pipelines for data ingestion and transformation.
• Monitor data workflows to detect failures, troubleshoot issues, and ensure SLA adherence.
• Implement data quality checks, validation, and governance policies for accuracy.
• Optimize data platforms (AWS/Azure/GCP, data lakes, warehouses) for performance and cost efficiency.
• Automate processes and support CI/CD practices for continuous DataOps improvement.

Required Skills

• 8–10 years of experience in Data Engineering or DataOps roles.
• Strong proficiency in Python with hands-on ETL/ELT pipeline development.
• Experience with cloud platforms: AWS, Azure, or GCP.
• Implementing DataOps practices for scalable, high-performance data systems.
• Bachelor’s degree in computer science, Engineering, Data Science, or related field.
• Collaborating with cross-functional teams to translate business needs into data solutions.
• Supporting analytics and reporting requirements.

Preferred Skills

• Experience with data lakes and warehouse optimization.
• Knowledge of data governance policies.

Key Skills

Education

Any Graduate