Securonix provides the Next Generation Security and Information Event Management (SIEM) solution. As a recognized leader in the SIEM industry, Securonix helps some of the largest global organizations detect sophisticated cyberattacks and rapidly respond to these attacks within minutes. With the Securonix SNYPR platform, organizations can collect billions of events each day and analyze them in near real-time to detect advanced persistent threats (APTs), insider threats, privilege account misuses and online fraud. Securonix pioneered the User and Entity Behavior Analytics (UEBA) market and holds patents in the use of behavioral algorithms to detect malicious activities. The Securonix SNYPR platform is built on big data Hadoop technologies and is infinitely scalable.
- Setting up and configuring multiple SOLR cores under Linux environment
- Indexing of unstructured data
- Defining SOLR index schemas for various data elements and configuring the same for various priorities.
- Studying, researching and resolving difficult issues involving Solr, Elastic and related technologies
- Engineer automated techniques and processes for the bulk indexing of large-scale data sets residing in database or un-indexed systems
- Hands on Automation using Python or Java
- Write automated unit test cases for solr search engine
- Load balancing, integrating multi core searches.
- Strong hands-on experience in SOLR/Elastic
- Expertise in SOLR/Elastic Collection Sharding/replication, failover, fault tolerance, high availability.
- Extensive Experience on Lucene & SOLR -Search Engine, Text Mining, Indexing Lucene Java search library, REST-like API such as HTTP/XML and JSON APIs
- Skill in indexing database on incremental manner. (Add indexes for new records added since previous index and removing indexes for the deleted records.)
- Expertise in configuring SOLR/Elastic schema and understanding in advanced schema fields.
- Understanding of internals of SOLR physical and logical layout
- Expertise in tuning the of search results.
- Expertise in Java JVM tuning and Debugging
- Deep understanding of HTTP and REST APIs.
- Expertise in fine tuning SOLR caches and cache warming and segment merging.
- Exposure to the internal implementations of SOLR/Elastic/Lucene
- Understanding of Information Retrieval techniques.
- Good understanding of agile development and continuous integration
- Good in depth understanding of the Linux in term of debugging tools and performance tuning
- Exposure with Big data platforms is required.
- Should have working knowledge of search and recommendations (Query parsing, Spell Check and associated search topics)
- Knowledge on indexing database using SOLRs built-in database indexing features.
- Good knowledge on Promoting search results, Facet searches, Pivot facet, Stats component, Boost queries, using Filter Queries etc
- SolrJ API programming experience for querying/feeding