Direct client requirement. We can schedule Immediate Interview
Hadoop Engineer
Need a Strong Java/Hadoop Architect. You should be technically very strong and have a good depth of knowledge. ETL,PL/SQL etc -you should understand technology as you will
be counted on to give suggestions on Technology decision.
The ideal candidate will be a seasoned Java programmer with strong Computer Science background (sorting, hashing, etc.) on the Unix platform;
also familiar with one or more functional languages (eg. Scala, Clojure) and ideally experienced with Hadoop MapReduce in particular.
He/she will also have a keen interest and/or actual hands-on experience with multiple distributed computing/storage frameworks (eg. Storm, Cassandra, HBase, Spark)
as well as Hadoop-specific DSLs (eg. Scoobi, Scrunch, Cascalog), and be motivated to solve complex problems involving large (long and wide) data sets,
efficiently and scalably.
Responsibilities
Design and implement a Hadoop-based ETL process.
Work with data scientists to re-implement machine-learned algorithms in MapReduce (coding in Java and/or higher level DSLs),or in other (appropriate) distributed
frameworks.
Design and implement a real-time event streaming system (with Hadoop integration).
Work with project managers and back-end/middle-tier engineers to develop and target data flow APIs.
Requirements
- Languages: Java.
- Scripting languages: Perl, Python or similar.
- CS algorithms: sorting, hashing, recursion, trees, graphs, etc.
- Hadoop core: MapReduce, HDFS.
- Hadoop utilities: Oozie, ZooKeeper.
- Relational algebra (SQL).
- Unix shell programming (sh, bash, csh, zsh): pipes, redirection, process control, etc.
- Unix pipeline utilities: awk, sed, grep, find, etc.
- Unix system utilities: cron, at, kill, ssh, sftp, etc.
- Regular expressions.
Desirable skills
- Hadoop cluster administration: queues, quotas, replication, block size, decommission nodes, add nodes, etc.
- JVM-based functional languages: Scala, Clojure.
- Hadoop pipeline frameworks: Streaming, Crunch, Cascading.
- Hadoop productivity frameworks: Scrunch, Scoobi.
- Hadoop query languages: Pig, Hive, Scalding, Cascalog, PyCascading.
- Hadoop libraries: Mahout.
- Alternative HDFS-based computing frameworks: Spark (Pregel).
- Serialization frameworks: Avro, Thrift, Protocol Buffers.
- Distributed databases: Cassandra, Voldemort, HBase, MongoDB, CouchDB.
- Real-time event streaming: Storm, S4, InfoSphere Streams (IBM).
- Statistics, data mining or machine learning: expectation, regression, clustering, etc.
Useful background skills
- Specific experience with the Cloudera Hadoop distribution.
- Unix system administration: sudo, mountd, bind, sendmail, etc.
- Database administration: MySQL, SQLite, Oracle, or similar.
Thanks!
Rituraj Borooah
___________________________________________________________
Google Group: Xrecnet - An IT Recruiters Network for US IT requirements.
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