Project Role : Data Engineer
Project Role Description : Design, develop and maintain data solutions for data generation, collection, and processing. Create data pipelines, ensure data quality, and implement ETL (extract, transform and load) processes to migrate and deploy data across systems.
Must have skills : PySpark
Good to have skills : NA
Minimum 3 year(s) of experience is required
Educational Qualification : 15 years full time education

Summary: As a Data Engineer, you will design, develop, and maintain data solutions for data generation, collection, and processing. Your typical day will involve creating data pipelines, ensuring data quality, and implementing ETL processes to migrate and deploy data across systems. You will play a crucial role in managing and optimizing data infrastructure to support the organization's data needs. Job Description: Responsibilities: 1. Develop, optimize, and maintain large-scale data processing pipelines using Apache Spark and Python or PySpark. 2. Write and maintain efficient, reusable, and reliable code to ensure the best possible performance and quality. 3. Collaborate with data engineers, data scientists, and other stakeholders to design and implement robust data solutions. 4. Perform data extraction, transformation, and loading (ETL) operations on large datasets. 5. Troubleshoot and resolve issues related to data processing and pipeline performance. 6. Implement best practices for data processing, including data validation, error handling, and logging. 7. Work with cloud-based data storage and processing platforms such as AWS, Azure, or Google Cloud. 8. Stay up to date with the latest industry trends and technologies to ensure the team is using the best tools and techniques available. Qualifications: 1. Bachelor’s degree in computer science, Information Technology, or a related field (or equivalent experience). 2. Proven experience as a PySpark Developer or in a similar role. 3. Strong proficiency in Python/pyspark programming and experience with Apache Spark. 4. Solid understanding of data processing concepts and ETL pipelines. 5. Experience with any cloud platforms such as AWS, Azure, or Google Cloud. 6. Proficiency in SQL and experience with relational and NoSQL databases. 7. Experience with version control systems like Git. 8. Familiarity with any big data tools and frameworks (e.g., Hadoop, Kafka). 9. Strong problem-solving skills and attention to detail. 10. Excellent communication and teamwork skills. 11. Familiarity with Agile development methodologies

15 years full time education

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