Data Engineer- Python Pyspark GCP

Role & responsibilities

• Develop and maintain scalable data pipelines using Python and PySpark.
• Design and implement ETL (Extract, Transform, Load) processes.
• Optimize and troubleshoot existing PySpark applications for performance.
• Collaborate with cross-functional teams to understand data requirements.
• Write clean, efficient, and well-documented code.
• Conduct code reviews and participate in design discussions.
• Ensure data integrity and quality across the data lifecycle.
• Integrate with cloud platforms like GCP, AWS or Azure.

Implement data storage solutions and manage large-scale datasets.

Preferred candidate profile

• 4 to 8 + Years of experience using Python and Pyspark.
• Strong proficiency in Python programming.
• Hands-on experience with PySpark and Apache Spark.
• Knowledge of Big Data technologies (Hadoop, Hive, Kafka, etc.).
• Experience with SQL and elational/non-relational databases.
• Familiarity with distributed computing and parallel processing.
• Understanding of data engineering best practices.
• Experience with REST APIs, JSON/XML, and data serialization.

Exposure to GCP services and cloud computing environments