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Responsibilities:

Design and implement distributed data processing pipelines using Spark, Hive, Python, and other tools and languages prevalent in the Hadoop ecosystem. Ability to design and implement end to end solution. Build utilities, user defined functions, and frameworks to better enable data flow patterns. Research, evaluate and utilize new technologies/tools/frameworks centered around Hadoop and other elements in the Big Data space. Build and incorporate automated unit tests, participate in integration testing efforts. Work with teams to resolving operational & performance issues Work with architecture/engineering leads and other teams to ensure quality solutions are implements, and engineering best practices are defined and adhered to.

Qualification:

MS/BS degree in a computer science field or related discipline 6+ years’ experience in large - scale software development 2+ year experience in Hadoop/Big Data Strong development skills around Hadoop, Spark, Hive 1+ years’ experience in workflow orchestration tools like Airflow Strong skills in Python, shell scripting, and SQL Experience with AWS components and services, particularly, EMR, S3, and Lambda Good understanding of file formats including Parquet, Avro, JSON and others Good understanding of R, TensorFlow, SAS or similar Experience with performance/scalability tuning, algorithms and computational complexity Experience (at least familiarity) with data warehousing, dimensional modeling and ETL development Proven ability to work cross functional teams to deliver appropriate resolution

Nice to have:

Front end UI development experience, specifically Node JS or Angular JS Machine learning frameworks