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At Karza technologies, we take pride in building one of the most comprehensive digital due-diligence platform by profiling millions of entities and trillions of associations amongst them using data collated from more than 700 publicly available government sources. Collated data is standardized using Karza Technologies- declarative in-house extract, transform, load (ETL) framework, which leverages container orchestration services to dynamically scale Kafka based consumers. Attributed to the wide variety of data driven use cases what Karza solves, it is not uncommon for us to look at the same set of data points from varying aspects by ensembling various data stores tuned for workloads like batch processing, network analysis, time series analysis, fuzzy searches and predictive analytics.
Must have skills :
- Solid understanding of data structures, algorithms, concurrency, distributed processing and data parallelism.
- Good conceptual understanding of NoSQL data stores like Key/Value stores, Document databases, Wide Column data stores, Graph databases and Search databases.
- Thorough understanding of at least one of the NoSQL data stores highlighted above (Preferable, if it includes Cassandra, Elastic Search, JanusGraph, Spark or Kafka).
- Should have practical experience of programming in at least one of the general purpose programming languages like Python, Java, Scala etc.
Highly desired but not mandatory :
- Containers and orchestration services.
- Experience of building auto-scalable event driven data pipelines.
- Good conceptual understanding of HDFS and Spark/MapReduce.
- Understanding of high volume data ingestion and streaming platforms.
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