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. 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.