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.