Embark on a career as a Data Engineer, focusing on designing, developing, and maintaining robust data solutions. This role is instrumental in managing data generation, collection, and processing.

You will be responsible for creating efficient data pipelines, ensuring the highest standards of data quality, and implementing sophisticated ETL processes. The goal is to seamlessly migrate and deploy data across various systems, optimizing data flow and accessibility.

This position requires a minimum of three years of hands-on experience in AWS BigData, demonstrating your expertise in cloud-based data solutions. A strong foundation in data engineering principles and a commitment to continuous learning are essential for success.

Design, develop, and maintain data solutions for data generation, collection, and processing. Create data pipelines and ensure data quality. Implement ETL processes to migrate and deploy data across systems. Possess strong experience in Data Engineering, ETL, and Data Quality processes. Demonstrate hands-on expertise in Python/Pyspark and SQL. Utilize AWS services like EMR, EC2, S3, and Glue for ETL processes. Perform independently and evolve into a Subject Matter Expert (SME). Actively participate and contribute to team discussions and problem-solving. Collaborate with stakeholders to gather and analyze requirements. Participate in code reviews to maintain code quality and best practices.

A minimum of three years of dedicated experience in AWS BigData is mandatory. Proficiency in AWS BigData is a core requirement. Solid understanding of cloud computing concepts and services. Experience with data processing frameworks like Apache Spark or Hadoop. Familiarity with database technologies, including SQL and NoSQL. Knowledge of data warehousing solutions and ETL processes is crucial. A total of 15 years of full-time education is required. Excellent communication skills are expected. Ability to work independently and as part of a collaborative team.