Hadoop Architect
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Other
Job Description
Job Description
Provides architectural and big picture oversight
and creates Architectural Specification for the development of new or enhanced
products and/or services.
Researches and evaluates new technologies,
design patterns, and software products to determine feasibility and
desirability of incorporating their capabilities within the company's products.
Identifies opportunities to implement and/or
enforce compliance of architectural standards, including Reference
Architecture, into customer and product enhancement or development projects.
Supports development and product teams by
providing high-level analysis and design reviews, performance, scalability and
benchmark test guidance, and subject matter expertise in technology and design.
Plans, directs and maintains projects. Reviews
work requests and estimates scope of projects.
Hands on experience working with Hadoop
Hortonworks 2.5 or higher
In-depth knowledge and understanding of Hadoop
Architecture and HDFS including YARN
Working knowledge of MapReduce, HBase, Pig,
Java, Hive, Zookeeper, Flume and Sqoop
Successful Big data deployments and
implementation strategies utilizing Hadoop life cycle model
Ability to perform analytics on data stored in
Hadoop via SQL queries
Experience working in core development Big Data
projects, Should be able to perform hands-on development activities in HDFS,
Hive, HBase, Spark, Scala, Map Reduce and Hadoop ETL development via tools is
plus.
Strong knowledge of programming and scripting
languages such as Java, Spark, Python, Hive, Pig
Experience with major big data technologies and
frameworks including but not limited to Hadoop, MapReduce, Pig, Hive, HBase,
Oozie, Mahout, Flume, ZooKeeper, MongoDB, and Cassandra;
Experience in working on production big data
solutions and experience in client-driven large-scale data lake implementation
projects;
Work with data engineering related groups in the
support of deployment of Hadoop and Spark jobs.
Deep understanding of Hadoop and Spark cluster
security, networking connectivity and IO throughput along with other factors
that affect distributed system performance
Strong working knowledge of disaster recovery,
incident management, and security best practices
Provides architectural and big picture oversight
and creates Architectural Specification for the development of new or enhanced
products and/or services.
Researches and evaluates new technologies,
design patterns, and software products to determine feasibility and
desirability of incorporating their capabilities within the company's products.
Identifies opportunities to implement and/or
enforce compliance of architectural standards, including Reference
Architecture, into customer and product enhancement or development projects.
Supports development and product teams by
providing high-level analysis and design reviews, performance, scalability and
benchmark test guidance, and subject matter expertise in technology and design.
Plans, directs and maintains projects. Reviews
work requests and estimates scope of projects.
Hands on experience working with Hadoop
Hortonworks 2.5 or higher
In-depth knowledge and understanding of Hadoop
Architecture and HDFS including YARN
Working knowledge of MapReduce, HBase, Pig,
Java, Hive, Zookeeper, Flume and Sqoop
Successful Big data deployments and
implementation strategies utilizing Hadoop life cycle model
Ability to perform analytics on data stored in
Hadoop via SQL queries
Experience working in core development Big Data
projects, Should be able to perform hands-on development activities in HDFS,
Hive, HBase, Spark, Scala, Map Reduce and Hadoop ETL development via tools is
plus.
Strong knowledge of programming and scripting
languages such as Java, Spark, Python, Hive, Pig
Experience with major big data technologies and
frameworks including but not limited to Hadoop, MapReduce, Pig, Hive, HBase,
Oozie, Mahout, Flume, ZooKeeper, MongoDB, and Cassandra;
Experience in working on production big data
solutions and experience in client-driven large-scale data lake implementation
projects;
Work with data engineering related groups in the
support of deployment of Hadoop and Spark jobs.
Deep understanding of Hadoop and Spark cluster
security, networking connectivity and IO throughput along with other factors
that affect distributed system performance
Strong working knowledge of disaster recovery,
incident management, and security best practices