• Design, develop, and maintain scalable data pipelines and ETL processes.
• Develop and optimize data processing solutions using Python and PySpark.
• Write complex and high-performing SQL queries for data extraction, transformation, and analysis.
• Work with large datasets and distributed computing frameworks to support data engineering initiatives.
• Collaborate with architects, analysts, and business stakeholders to deliver data-driven solutions.
• Troubleshoot and resolve performance, scalability, and data quality issues.
• Contribute to data platform modernization and best practices.
Skills
• 5–13 years of experience in Data Engineering or related roles.
• Solid hands-on experience in Python development.
• Proven experience with PySpark for large-scale data processing.
• Robust knowledge of SQL, including query optimization and performance tuning.
• Exposure to or working knowledge of Scala.
• Experience working with cloud-based or enterprise data platforms.
• Solid analytical, problem-solving, and communication skills.
Preferred Skills
• Experience with data warehousing and ETL frameworks.
• Exposure to cloud platforms such as Azure, AWS, or GCP.