We are looking for a skilled Data Engineer with expertise in AWS/Azure environments to build and optimize large-scale data processing pipelines. The ideal candidate will have strong analytical skills, deep knowledge of data structures and algorithms, and hands-on experience with Python and PySpark.

Key Responsibilities:

• Design, develop, and maintain scalable data pipelines and ETL processes.
• Implement data solutions leveraging AWS or Azure cloud services.
• Optimize data workflows and address bottlenecks in existing systems.
• Collaborate with data scientists, analysts, and other engineers to ensure data availability and reliability.
• Write clean, efficient, and reusable code following best practices.
• Monitor data integrity, performance, and availability.

Required Skills:

• Strong proficiency in Python for data manipulation and scripting.
• Hands-on experience with PySpark for large-scale data processing.
• Solid understanding of Data Structures and Algorithms.
• Experience working with AWS/Azure services for data engineering.
• Knowledge of SQL and NoSQL databases.
• Ability to troubleshoot and optimize data workflows.

Preferred Qualifications:

• 3+ years of relevant work experience.
• Certifications in AWS or Azure (e.g., AWS Certified Data Analytics, Azure Data Engineer Associate).
• Experience with tools like Apache Airflow, Databricks, or similar.
• Familiarity with containerization tools (e.g., Docker, Kubernetes)