
Big Data Engineer
AgileEnterpriseSolutions · Pittsburgh, PA, United States
Weak hiring record · median 3812 days open
All reasons
- Open 3358 days
- 100% of this employer's openings are over 60 days old
In its favour
- Still listed on the employer's own board
Hi,
Hope your are doing great!
My name is Shyam and I am a Professional Recruiter at Agile, Inc. I have an open opportunity that you may be a good fit for. I came across your resume and think that you might be a good fit for the position listed below.
Title: Big Data Engineer
Location: Pittsburgh, PA
Mode: Permanent
Job Description
We are looking for a Big Data Engineer that will work on the collecting, storing, processing, and analyzing of large sets of data.
The primary focus will be on choosing optimal solutions to use for these purposes, then maintaining, implementing, and monitoring them.
You will also be responsible for integrating them with the architecture used across the company.
Skills and Qualifications
- Proficient understanding of distributed computing principles
- Management of Hadoop cluster (Cloudera preferred), with all included services
- Ability to solve any ongoing issues with operating the cluster
- Proficiency with Hadoop v2, MapReduce, HDFS, Sqoop
- Experience with building stream-processing systems, using solutions such as Storm or Spark-Streaming
- Good knowledge of Big Data querying tools, such as Pig, Hive, and Impala
- Experience with Spark
- Experience with integration of data from multiple data sources such as MsSQL Server, Oracle,
- Good understanding of SQL queries, joins, stored procedures, relational schemas
- Experience with NoSQL databases, such as HBase, Cassandra, MongoDB (preferred)
- Knowledge of various ETL techniques and frameworks, such as Flume
- Experience with various messaging systems, such as Kafka or RabbitMQ
- Experience with Cloudera FS domain knowledge a big plus but not required
Thanks & Regards
All your information will be kept confidential according to EEO guidelines.
Skills
- Hadoop
- HDFS
- Storm
- Spark
- Hive
- SQL Server
- Oracle Database
- SQL
- HBase
- Cassandra
- MongoDB
- ETL
- Kafka
- RabbitMQ
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