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We are seeking a skilled and experienced Data Engineer to join our team. The ideal candidate will have expertise in Big Data platforms and a strong background in designing, developing, and maintaining data pipelines. You will be responsible for ensuring data quality, optimizing data workflows, and working with distributed data systems. This role requires a deep understanding of modern data engineering workflows, ETL processes, and large-scale data processing.
Job Responsibility:
Design, develop, and maintain scalable and efficient data pipelines
Implement ETL/ELT processes to extract, transform, and load data from various sources
Optimize data workflows for performance, scalability, and reliability
Work with Big Data technologies to process and analyze large datasets
Develop distributed data processing pipelines using Spark and MapReduce
Integrate data from multiple sources including APIs, flat files, and third-party systems
Ensure data accuracy, consistency, and integrity across systems
Implement data validation and error-handling mechanisms
Document data pipelines, data designs, and processes
Requirements:
7-9 years of relevant experience
Expertise in Big Data platforms: Hadoop, Spark (PySpark/Scala), Hive, or HDFS
Proficiency in SQL and database design principles
Experience with ETL/ELT tools (e.g., Informatica, Talend, or Python-based ETL frameworks)
Proficiency in scripting languages such as Python, Scala, or Shell scripting
Knowledge of data quality, data governance, and data security best practices
Experience in systems analysis and programming of software applications
Experience in managing and implementing successful projects
Working knowledge of consulting/project management techniques/methods
Ability to work under pressure and manage deadlines or unexpected changes
Bachelor's degree/University degree or equivalent experience
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