Data Engineer

About the Role

As a Data Engineer II at Baazi, you will contribute to building and optimizing scalable data pipelines and lakehouse systems that power analytics and product insights across the organization. You’ll work hands-on across our AWS-based ecosystem, develop robust data workflows, and ensure high standards of data quality, performance, and reliability.

Key Responsibilities

• Build and optimize scalable data pipelines and lakehouse components using

  Iceberg or Hudi

  .
• Develop ETL/ELT workflows on AWS using

  Glue, EMR, Lambda, Redshift

  , and other platform services.
• Write clean, modular, reusable code using

  PySpark, Python, and SQL

  .
• Manage and enhance orchestration workflows with

  Airflow

  to ensure reliability and scalability.
• Collaborate with analytics, product, and engineering teams to maintain unified and consistent data models.
• Participate in

  performance tuning, cost optimization

  , and improvement of AWS data infrastructure.
• Implement and follow best practices in

  data quality, cataloging, and metadata management

  .
• Contribute to code reviews and engineering discussions to maintain high technical standards.

Required Skills & Experience

• 2–4 years

  of experience in data engineering with strong exposure to large-scale data systems.

• 2+ years of hands-on experience in PySpark

  .
• Solid understanding of the

  AWS data ecosystem

  : Glue, EMR, S3, Lambda, Redshift, CloudWatch.
• Practical experience working with

  Apache Iceberg or Hudi

  (Iceberg preferred).
• Strong programming skills in

  Python, PySpark

  , and solid command over

  SQL

  .
• Experience working with

  Airflow

  for scheduling and orchestration.
• Understanding of distributed systems, data modeling, and data governance principles.
• Exposure to

  containerized environments (Kubernetes, Docker)

  is a plus.
• Ability to work closely with business and technical teams to deliver scalable solutions.