Description

You will own the design, implementation, and reliability of scalable ELT/ETL pipelines for enterprise analytics.

This role is on-site.

Responsibilities

• Lead the end-to-end delivery of data engineering projects, from requirements gathering through production deployment and post-release support.
• Build and maintain resilient data pipelines using Python, SQL, Airflow, and AWS cloud-native services.
• Define and execute data testing strategies, including unit, integration, regression, and UAT, to ensure data integrity.
• Improve workflow reliability through observability, automation, incident triage, and SLA-driven resolution.

Required Skills

• 9-12 years of experience in data engineering, data design, and analytics platforms.
• 5+ years of hands-on experience with Python and SQL.
• 4+ years of experience with AWS and Airflow.
• Strong understanding of ETL and ELT pipeline development for analytics-ready data assets.
• Proficiency in data modeling, data integrity, and transformation logic.
• Experience with Git-based version control and CI/CD workflows.
• Bachelor's degree in Computer Science, Engineering, or a related field.

Preferred Skills

• Experience with enterprise analytics and reporting tools (e.g., Tableau, MicroStrategy).
• Familiarity with agile delivery environments.

Key Skills

Education

Any Graduate