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, efficient, 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.
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Applications Development ------------------------------------------------------
Time Type:
Full time ------------------------------------------------------
Most Relevant Skills
Please see the requirements listed above. ------------------------------------------------------
Other Relevant Skills
For complementary skills, please see above and/or contact the recruiter. ------------------------------------------------------
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