Description

Engineer data and AI solutions for analytics, building scalable pipelines and managing cloud-native infrastructure.

This role is on-site.

Responsibilities

• Design and build scalable batch and streaming data pipelines for real-time and near-real-time analytics.
• Develop and optimize ETL/ELT workflows for structured and unstructured data from MongoDB, PostgreSQL, APIs, and third-party systems.
• Architect and manage cloud-native data infrastructures using GCP services like BigQuery, Dataflow, Cloud Composer, and Cloud Storage.
• Implement monitoring, logging, and observability frameworks to ensure data quality and governance.
• Collaborate with analytics and product teams to define data requirements and deliver analytics-ready datasets.

Required Skills

• 4-6 years of hands-on experience in data engineering and big data technologies.
• Strong proficiency in Python and SQL.
• Experience with ETL/ELT development and building data connectors across relational and non-relational databases.
• Proven experience with Google Cloud Platform services (BigQuery, Dataflow, Cloud Composer, Pub/Sub).
• Experience with MongoDB and PostgreSQL.
• Familiarity with API integrations.

Preferred Skills

• Experience with unstructured data processing.

Key Skills

Education

Any Graduate