Job Description: As a Data Engineer at our company, you will be responsible for building and optimizing data pipelines using Apache Spark and SQL. You should have a minimum of 3 years of hands-on experience in this field. Your primary focus will be on batch data processing, Data Streaming, data reliability, and performance optimization. You will work closely with different teams to create scalable data solutions that align with the company's analytics and business goals. Key Responsibilities: - Utilize Apache Spark, including SparkSQL, for developing and optimizing data pipelines. - Demonstrate strong SQL skills by writing complex and optimized queries. - Implement batch processing techniques, including scheduling, managing dependencies, and performance tuning. - Design data pipeline architecture and ensure its scalability. - Handle structured and semi-structured data formats such as CSV, JSON, and Parquet. Qualifications Required: - Minimum 3 years of experience with Apache Spark, particularly in SparkSQL. - Proficiency in SQL for writing efficient queries. - Prior exposure to batch processing methodologies and performance optimization. - Understanding of data pipeline fundamentals. - Familiarity with structured and semi-structured data formats. About the Company: Unfortunately, the additional details about the client were not provided in the job description.,

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Data Engineer