Data Engineer

Key Responsibilities:

• Design, develop, and maintain

  highly scalable ETL pipelines

  for telecom data processing.
• Implement

  data ingestion, transformation, and integration workflows

  using

  Python and PySpark

  .
• Work with

  AWS cloud services

  (S3, Glue, EMR, Redshift, Athena, Lambda, etc.) to manage and optimize big data solutions.
• Collaborate with product teams, data scientists, and business stakeholders to deliver data-driven solutions for network optimization, customer analytics, and business insights.
  
• Ensure

  data quality, reliability, and governance

  in all data systems.
• Optimize data pipelines for

  scalability, performance, and cost-efficiency

  in a telecom-scale environment.
• Monitor and troubleshoot data workflows, ensuring minimal downtime and high availability.
  

Required Skills & Qualifications:

• 6 to 8 years

  of proven experience as a

  Data Engineer

  .
• Strong hands-on expertise in

  Python

  and

  PySpark

  .
• Advanced knowledge of

  AWS data ecosystem

  (S3, Glue, EMR, Lambda, Redshift, Athena).
• Solid experience in designing and maintaining

  ETL pipelines

  and big data workflows.
• Strong knowledge of

  data warehousing concepts, big data frameworks, and distributed data processing

  .
• Proficiency in

  SQL

  and experience with performance tuning.
• Familiarity with CI/CD processes and version control (Git).
  
• Excellent problem-solving, communication, and collaboration skills.
  

Preferred candidate profile

Notice period : 1 Month or less / Currently serving