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Data Engineer
4 weeks ago
Primary_skills(Must_have)
Key Responsibilities :
Advanced PySpark Development:
Write Efficient PySpark Code: Develop high-quality, reusable, and scalable PySpark scripts to process large datasets.
Custom Transformations: Design and implement custom transformations and user-defined functions (UDFs) to meet specific data processing requirements.
Data Frame Manipulation: Utilize PySpark DataFrame APIs to perform complex data manipulations, aggregations, and joins.
Error Handling and Logging: Implement robust error handling and logging mechanisms within PySpark applications to ensure reliability and ease of troubleshooting.
Develop and Maintain Data Pipelines:
Design, build, and optimize robust and scalable data pipelines using PySpark.
Implement ETL processes to ingest, transform, and load data from various sources.
Performance Optimization:
Optimize PySpark jobs for performance and efficiency, including tuning Spark configurations and optimizing resource utilization.
Conduct code reviews and performance assessments to identify and implement improvements in PySpark codebases.
Data Processing and Analysis:
Perform data cleaning, validation, and transformation using PySpark to ensure data quality and consistency.
Collaborate with data analysts and scientists to understand data requirements and deliver PySpark-based solutions.
Integration and Deployment:
Integrate PySpark applications with other data tools and platforms, ensuring seamless data flow across systems.
Participate in the deployment and maintenance of PySpark applications in production environments, ensuring scalability and reliability.
Collaboration and Documentation:
Work closely with cross-functional teams including data engineers, software developers, and business stakeholders to deliver comprehensive data solutions.
Document PySpark code, processes, workflows, and technical specifications to ensure maintainability and knowledge sharing.
Preferred Skills
Advanced Analytics:
Experience with machine learning libraries and frameworks.
DevOps Practices:
Familiarity with CI/CD pipelines and containerization technologies (e.g., Docker, Kubernetes).
Soft Skills:
Strong problem-solving abilities and attention to detail.
Excellent communication and teamwork skills.
Ability to manage multiple tasks and meet deadlines in a fast-paced environment.
