Description tasks and responsibilities of the position:
- Responsible for defining and maintaining both infrastructure (either in the cloud, on-premise or hybrid), as the architecture of components in each project Big Data, to support both batch processes, and real-time streaming.
- Responsible for installation tasks, deployment, maintenance (evolutive and corrective), execution, and ultimately operational necessary to ensure the proper functioning of the various Big Data systems that support to analytical and data processes.
- It will be updated the latest trends and technologies in Big Data ecosystem and proposing new solutions and variants to existing Big Data architectures and deploy.
- Solid computer skills and Systems Architecture.
- Experience in the deployment and maintenance of Big Data systems: Hadoop and Spark.
- Knowledge in management level distributions Big Data market (at least 1): Cloudera, Hortonworks, MapR, Pivotal, IBM
- Knowledge in management level data bases NoSQL (at least 1): MongoDB, Cassandra, CouchDB, Redshift, HBase, etc.
- Management Tools Hadoop (at least 1): Zookeper, Oozie, Ambari, …
- Data Manipulation (at least 2): SQL, Hive, Pig, Impala, SparkQL, Sqoop, Flume, Hue, Web Scraping, etc.
- Programming Languages (at least 1): Java, Python, scripting in general.
Desirable Technical requirements:
- Knowledge in management level in several distributions Big Data and data bases NoSQL.
- Programming Languages: Any addition to the above, plus Julia, Scala or R.
- Knowledge in Management Gephi, Neo4j, QlikView, Tableau, Elasticsearch, Lucene, Solr, etc.
- Knowledge in management in Analytics and Data Mining tools: KNIME, RapidMiner, SPSS, SAS, Statistic, MATLAB.
- Other technologies Big Data: Logstash, STORM, Kafka, etc.
- Experience in programming against third-party APIs.
- Basic knowledge of Statistics & Machine Learning.
- Computer Engineering, Telecommunications Engineering or Superior.
- Courses and certifications in any of the Big Data ecosystem technologies and handling techniques and data analysis will be evaluated.
- 2-3 years in data analytics projects that have used Big Data systems and technologies
- Experience will be valued in projects that have been analyzed large volumes of data from heterogeneous sources will be evaluated.
- Fluent English
- Valuable: Knowledge of the financial sector and in general will be appreciated, any project experience Big Data and Data Management in Banks and Insurance.