- Robust 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 of data engineering best practices.
- Experience with REST APIs, JSON/XML, and data serialization.
- Exposure to cloud computing environments.
- 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