We are seeking a highly skilled and experienced BigData/PySpark Engineer to join our dynamic Big Data Analytics team. This role is pivotal in designing, developing, and optimizing robust, scalable data pipelines for large-scale data processing and analytics.

Key Responsibilities:
- Design & Development: Create and optimize scalable ETL (Extraction, Transformation, Loading) pipelines using PySpark for massive datasets.
- Coding & Engineering: Write clean, effective, well-documented code primarily in Python (PySpark) often leveraging frameworks/tools.
- Collaboration: Work with cross-functional teams (senior developers, data engineers, analysts, business partners) to understand data requirements and ensure seamless solution integration.
- Troubleshooting & Optimization: Debug and resolve data processing issues and performance bottlenecks in Spark applications and other big data technologies.
- Full SDLC Involvement: Participate in the entire software development lifecycle, from requirements analysis and design to testing, deployment, and operations.
- Data Integrity:



Ensure high data quality and integrity throughout the data lifecycle.

This candidate possesses
4-8 years of experience
in developing and managing Enterprise Applications, demonstrating a robust foundation in Big Data technologies and a strong grasp of software development principles.

Key Experience & Expertise:
- Enterprise Application Development: 4-8 years in developing and managing enterprise-grade applications.
- Object-Oriented Programming (OOP): Solid foundation in OOP concepts.
- Big Data Development: Expertise in PySpark, HDFS, Hive, Sqoop, and Hadoop for Big Data environments.
- Database Technologies: Good exposure to SQL Server and ORACLE databases. Experience with query writing for data validation/manipulation
- Scripting & Automation: Proficient in Shell Scripting and experience with job scheduling tools like Autosys.
- BI Reporting Tools: Some exposure to BI tools, specifically Tableau.
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📌 PySpark Big Data Developer (Pune Division)
🏢 Citi
📍 Pune Division