Pyspark Developer @ Maveric

Job Description

Job Summary:

We are seeking a skilled and experienced PySpark Developer with 3 to 5 years of hands-on experience in building and optimizing distributed data pipelines, data processing workflows, and data validation using Apache Spark with Python (PySpark). The ideal candidate should have strong analytical and problem-solving skills, and be proficient in handling large-scale datasets, performing transformations, and ensuring data quality across distributed systems.

Key Responsibilities:

• Develop, maintain, and optimize PySpark scripts for distributed data processing, cleansing, and validation.
• Work extensively with Spark Data Frames for data wrangling, aggregation, and transformation.
• Design and implement scalable ETL pipelines to process large datasets from diverse sources (e.g., HDFS, S3, Kafka).
• Collaborate with data analysts, data scientists, and business teams to understand data requirements and deliver reliable solutions.
• Ensure performance optimization through partitioning, caching, and efficient Spark job tuning.
• Write unit tests and implement robust error handling and logging mechanisms.
• Debug and troubleshoot Spark jobs and data-related issues to ensure accuracy and consistency.
• Document data workflows, pipeline architecture, and transformation logic for future reference.
• Contribute to process improvements and propose new approaches for distributed data handling and performance enhancement.

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Keyskills:   Data Validation Pyspark Hadoop HDFS Kafka