Data Engineer - Pyspark ETL Hadoop Python SQL

We are seeking a skilled PySpark Developer to join our Data Engineering team. The ideal candidate should possess strong hands-on experience in PySpark, Python, and SQL, with expertise in developing scalable data processing solutions and ETL pipelines. The candidate will be responsible for designing, developing, optimizing, and maintaining high-performance data applications that support enterprise analytics and business intelligence initiatives.

Key Responsibilities :

- Design, develop, and maintain scalable ETL/ELT pipelines using PySpark.

- Develop data processing solutions for large-scale structured and unstructured datasets.

- Build, optimize, and troubleshoot Spark applications for performance and scalability.

- Perform data extraction, transformation, validation, and loading activities.

- Develop reusable and efficient data engineering frameworks and components.

- Collaborate with business analysts, data architects, and cross-functional teams to understand data requirements.

- Ensure data quality, integrity, and governance across data platforms.

- Monitor and support production data pipelines and resolve performance bottlenecks.

- Participate in code reviews and follow best practices for development and deployment.

Required Skills :

- Strong hands-on experience with PySpark

- Proficiency in Python

- Strong knowledge of SQL

- Experience with ETL/Data Engineering projects

- Good understanding of Data Warehousing concepts

- Experience with Spark SQL, DataFrames, and distributed data processing

- Knowledge of performance tuning and optimization techniques in Spark

- Experience working in Linux/Unix environments

- Strong analytical and problem-solving skills