Responsibilities As a Big Data Engineer, you will develop, maintain, evaluate, and test big data solutions. You will be involved in data engineering activities like creating pipelines/workflows for Source to Target and implementing solutions that tackle the clients needs. Your primary responsibilities include: Design, build, optimize and support new and existing data models and ETL processes based on our clients business requirements. Build, deploy and manage data infrastructure that can adequately handle the needs of a rapidly growing data driven organization. Coordinate data access and security to enable data scientists and analysts to easily access to data whenever they need too Required education Bachelor's Degree Preferred education Master's Degree Required technical and professional expertise Strong proficiency in Python:Expertise in Python programming with a focus on data processing and manipulation. Experience with Apache Spark (PySpark):In-depth knowledge of Sparks architecture, core APIs, and PySpark for distributed data processing. Big Data Technologies:Familiarity with Hadoop, HDFS, Kafka, and other big data tools. Data Engineering Skills:Strong understanding of ETL pipelines, data modeling, and data warehousing concepts. SQL Proficiency:Experience writing optimized SQL queries for large-scale data analysis and transformation. Data Processing Frameworks:Knowledge of data processing libraries such as Pandas, NumPy, and Dask. Cloud Platforms:Experience working with cloud platforms like AWS, Azure, or GCP, including using cloud storage systems Preferred technical and professional experience Understanding of Devops. Experience in building scalable end-to-end data ingestion and processing solutions Experience with object-oriented and/or functional programming languages, such as Python, Java and Scala

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