Karza Technologies_Data Engineer

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 a combination of data stores tuned for workloads like batch processing, network analysis, time series analysis, fuzzy searches and predictive analytics.

Some other highlights include:
● Recognized as Top25 startups to work with, 2019 by LinkedIn
● Only startup in Yes Bank Global Fintech Accelerator (Autumn Cohort) 2018 to sign a contract at the end of the program
● One of eight startups shortlisted from over 200, in Citi India FinTech Challenge 2018 by Citibank
● Awarded second runner-up in the first batch of Viacom18's Startup Engagement Programme VStEP, in addition to signing a contract at the end of the program
● Winner of FinTech Spot Pitches at Fintegrate Zone 2018 held at Bombay Stock Exchange
● Winner of FinShare 2018 challenge held by ShareKhan

Must have skills:
● Solid understanding of data structures, algorithms, concurrency, distributed processing and data parallelism .
● Good conceptual understanding of a subset of NoSQL data stores like search, graph,wide-column, key/value and document databases.
● Thorough understanding of at least one of the NoSQL data stores- Preferable, if it includes Cassandra, Elastic Search, JanusGraph, Spark or Kafka.
● Should be proficient 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.
● Deep interest in Graph algorithms and mathematics.
● Should be comfortable in going through open source code and reading research papers.