Job Description
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.
Solid 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.
Robust 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.