Description

You will design, build, and maintain scalable data architectures and pipelines across cloud environments.

This role is on-site.

Responsibilities

• Build ETL pipelines using Python and Spark for file-based and streaming architectures.
• Store large datasets optimally using Parquet, JSON, or Avro formats.
• Expose big data as tables using Hive, Iceberg, or Glue.
• Deploy data pipelines leveraging AWS, GCP, and Azure technologies.
• Collaborate with Data Analysts, Data Scientists, and Governance teams to ensure data availability and scalability.

Required Skills

• 10+ years of experience in Data Engineering.
• 2+ years of experience building ETL pipelines for Data Lakes or Data Warehouses.
• 2+ years of professional Python experience.
• 2+ years of experience with Spark.
• Strong knowledge of Oracle and MongoDB.
• Background in building data platforms in AWS, GCP, or Azure.
• Familiarity with Parquet, Avro, and JSON file formats.

Preferred Skills

• Experience building RAG-based tools.

Key Skills

Education

ANY GRADUATE