We are seeking an experienced Data Engineer with strong expertise in Python, PySpark, AWS, Glue, Redshift, and Kafka. The ideal candidate will be responsible for designing and implementing large-scale data pipelines, ensuring data quality, and enabling real-time and batch data processing in a cloud environment. This is a highly technical role requiring strong problem-solving skills and the ability to collaborate with business and technology stakeholders.

REQUIRED SKILLS & QUALIFICATIONS

• 5+ years of experience as a Data Engineer in cloud-based environments.
• Strong hands-on expertise with Python and PySpark for data transformation.
• Proven experience with AWS services (Glue, Redshift, S3, Lambda, EMR, IAM).
• Expertise in Kafka for real-time event streaming and processing.
• Solid knowledge of data warehousing concepts, schema design, and performance tuning.
• Strong experience with SQL (Redshift/PostgreSQL/MySQL).
• Knowledge of CI/CD pipelines and version control (Git, Jenkins, etc.).
• Excellent analytical and communication skills.
  Job Type: Contract
  Pay: $60.00 - $70.00 per hour
  Expected hours: 40 per week
  Work Location: In perso

• Design, develop, and maintain scalable ETL/ELT pipelines using Python, PySpark, and AWS Glue.
• Build and manage data warehouses and data lakes on AWS (Redshift, S3, Glue Catalog).
• Implement real-time streaming pipelines using Apache Kafka.
• Optimize performance of data pipelines and queries for large datasets.
• Work closely with analysts, data scientists, and business teams to deliver clean, reliable, and well-structured data.
• Ensure data governance, quality, and security standards are followed.
• Automate data workflows and monitoring to improve reliability and efficiency.
• Troubleshoot and resolve complex data pipeline issues in production.