Description

You will build and scale data pipelines, analytics platforms, and ML systems.

This role is on-site.

Responsibilities

• Design and build scalable data pipelines and analytics platforms.
• Define technical direction and best practices for data and ML engineering.
• Partner with data scientists, business, and IT teams cross-functionally.
• Ensure project delivery meets governance and security standards.

Required Skills

• 7+ years in high-performance, data-heavy backend systems.
• 5+ years hands-on experience with big data tools including Spark, Hadoop, AWS Glue, EMR, Snowflake, Databricks, and ADF.
• Strong knowledge of ML lifecycle, CI/CD, and MLOps.
• Experience designing scalable architectures in AWS or Azure.
• Familiarity with backend frameworks (FastAPI, Flask, Node.js, Spring Boot).
• Bachelor’s in Computer Science, Engineering, or related field.

Preferred Skills

• AWS SageMaker or LLM deployment experience.
• Full-stack development exposure.

Key Skills

Education

Any Graduate