Description

You will lead complex data engineering initiatives, designing scalable pipelines and cloud-based analytics platforms. You own the technical direction for data infrastructure, ensuring security, governance, and performance across AWS and Azure environments.

Responsibilities

• Architect and manage cloud-based analytics platforms and data infrastructure on AWS and Azure.
• Design, build, and maintain secure, scalable data pipelines using PySpark and ETL frameworks.
• Define standards and best practices for ETL development, data modeling, and warehouse design.
• Perform logical and physical data modeling, including source-to-target mappings and schema definitions.
• Mentor junior engineers and guide implementation partners on technical execution.

Required Skills

• 10+ years of experience in data engineering and data platform development.
• Strong hands-on expertise in ETL development and big data processing with PySpark.
• Proficiency in SQL with a deep understanding of database internals.
• Experience with AWS services: EMR, Redshift, S3, and Postgres.
• Experience designing and optimizing large-scale data warehouses.
• Strong understanding of distributed systems and cloud-based architectures.
• Ability to conduct performance analysis, optimization, and tuning of data platforms.

Preferred Skills

• Exposure to Azure data services.
• Experience leading teams and managing stakeholder expectations.

Key Skills

Education

Any Graduate