AWS Data Engineer

• Design and build scalable ETL pipelines and data integration workflows using AWS services and Python.
  
  
• Develop and optimize data lake and data warehouse solutions for structured and unstructured data.
  
  
• Leverage Apache Spark for large-scale data processing and transformation tasks.
  
  
• Collaborate with cross-functional teams to gather requirements and deliver clean, usable datasets for analytics and reporting.
  
  
• Ensure high data quality, security, and compliance in all stages of the data lifecycle.
  
  

Requirements

• 5+ years of hands-on experience in data engineering roles.
  
  
• Proficiency in Python for building and automating data pipelines.
  
  
• Strong experience with AWS services (S3, Glue, Redshift, Lambda, etc.).
  
  
• Solid understanding of ETL processes and modern data warehousing concepts.
  
  
• Experience with big data tools, especially Apache Spark (PySpark preferred).
  
  
• Familiarity with DevOps and CI/CD practices for data pipeline deployment.
  
  
• Knowledge of data governance and cataloging tools.
  
  
• Strong problem-solving, communication, and collaboration skills.