· 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.
· MS/BS degree in a computer science field or related discipline
· 6+ years’ experience in large-scale software development
· 1+ year experience in Hadoop
· Strong Java programming, Python, shell scripting, and SQL
· Strong development skills around Hadoop, Spark, MapReduce, Hive, and Pig
· Strong understanding of Hadoop internals
· Good understanding of file formats including JSON, Parquet, Avro, and others
· Experience with databases like Oracle
· Experience with performance/scalability tuning, algorithms and computational complexity
· Experience (at least familiarity) with data warehousing, dimensional modeling and ETL development
· Ability to understand and ERDs and relational database schemas
· Proven ability to work cross functional teams to deliver appropriate resolution
Nice to have:
· Experience with AWS components and services, particularly, EMR, S3, and Lambda
· Experience with open source NOSQL technologies such as HBase, DynamoDB, Cassandra
· Experience with messaging & complex event processing systems such as Kafka and Storm
· Automated testing, Continuous Integration / Continuous Delivery
· Machine learning frameworks
Statistical analysis with Python, R or similar