Developer

Must-Have**

• 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 relational/non-relational databases.

• Familiarity with distributed computing and parallel processing.

• Understanding data engineering best practices.

• Experience with REST APIs, JSON/XML, and data serialization.

• Exposure to cloud computing environments.

• 5+ years of experience in Python and PySpark development.

• Experience with data warehousing and data lakes.

• Knowledge of machine learning libraries (e.g., MLlib) is a plus.

• Strong problem-solving and debugging skills.

• Excellent communication and collaboration abilities.

Requirements

• 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 AWS, Azure, or GCP.

Implement data storage solutions and manage large-scale datasets.