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Job Location | Pune |
Education | Not Mentioned |
Salary | Not Disclosed |
Industry | Recruitment Services |
Functional Area | IT Operations / EDP / MIS |
EmploymentType | Full-time |
Proficient understanding of distributed computing principles Management of Hadoop cluster, with all included services {{unless you are going to havespecific Big Data DevOps roles for this}} Ability to solve any ongoing issues with operating the cluster {{unless you are going tohave specific Big Data DevOps roles for this}} Proficiency with Hadoop v2, MapReduce, HDFS Experience with building stream-processing systems, using solutions such as Storm orSpark-Streaming {{if stream-processing is relevant for the role}} Good knowledge of Big Data querying tools, such as Pig, Hive, and Impala Experience with Spark {{if you are including or planning to include it}} Experience with integration of data from multiple data sources Experience with NoSQL databases, such as HBase, Cassandra, MongoDB Knowledge of various ETL techniques and frameworks, such as Flume Experience with various messaging systems, such as Kafka or RabbitMQ Experience with Big Data ML toolkits, such as Mahout, SparkML, or H2O {{if you aregoing to integrate Machine Learning in your Big Data infrastructure}} Good understanding of Lambda Architecture, along with its advantages and drawbacks Experience with Cloudera/MapR/HortonworkResponsibilities:We are looking for a Data Engineer that will work on collecting, storing, processing, andanalyzing huge sets of data. The primary focus will be on choosing optimal solutions to use forthese purposes, then maintaining, implementing, and monitoring them. You will also beresponsible for integrating them with the architecture used across the company.Experience Requirements:Selecting and integrating any Data tools and frameworks required to provide requestedcapabilities Implementing the ETL process Monitoring performance and advising any necessary infrastructure changes Defining data retention policies,
Keyskills :
process monitoringjavasqldata warehousingdata retentionmachine learningpythoninformaticamonitoring performancepigetlsparkbig datahive