Description
Design and implement distributed data processing pipelines using Spark, Hive, Sqoop, 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.
Define and build data acquisitions and consumption strategies
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
1+ year experience in Hadoop or big data technologies.
Strong Java programming, Python, Shell Scripting, and SQL
Strong development skills around Hadoop, Spark, Hive, and Pig
Good understanding of file formats including JSON, Parquet, Avro, and others
Experience with performance/scalability tuning, algorithms and computational complexity
Ability to understand relational database schemas
Proven ability to work cross functional teams to deliver appropriate resolution
Experience with AWS components and services, particularly, EMR, S3, and Lambda
Automated testing, Continuous Integration/Continuous Delivery
English speaking project. Please reply for further details