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Studios - Data Engineer - Hive/Spark

2 weeks ago


Bengaluru, Karnataka, India CAW Full time US$ 90,000 - US$ 1,20,000 per year

Job Description
We are looking for a savvy Data Engineer to join our growing team, responsible for expanding and optimizing our data and data pipeline architecture, as well as optimizing data flow. The ideal candidate is an experienced data pipeline builder and data wrangler who enjoys optimizing data systems and building them from the ground up. The right candidate will be excited by the prospect of optimizing or even re-designing our company's data architecture to support our next generation of products and data :

  • Create and maintain optimal data pipeline architecture.
  • Create and maintain events/streaming-based architecture/design.
  • Identify, design, and implement internal process improvements : automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
  • Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and AWS big data technologies.
  • Create data tools for analytics and data scientist team members that assist them in building

and optimizing our product into an innovative industry leader.

  • Work with data scientists to strive for greater functionality in our data systems.

Requirements

  • We are looking for a candidate with 2+ years of experience in a Data Engineer role.
  • Experience with big data tools : HDFS/S3 Spark/Flink, Hive, Hbase, Kafka/Kinesis, etc.
  • Experience with relational SQL and NoSQL databases, including Elasticsearch and Cassandra/Mongodb.
  • Experience with data pipeline and workflow management tools : Azkaban, Luigi, Airflow, etc.
  • Experience with AWS /GCP cloud services.
  • Experience with stream-processing systems : Spark-Streaming/Flink, etc.
  • Experience with object-oriented/object function scripting languages : Java, Scala, etc.
  • Experience building and optimizing big data pipelines, architectures, and data sets.
  • Strong analytic skills related to working with structured/unstructured datasets.
  • Build processes supporting data transformation, data structures, dimensional modeling,

metadata, dependency, schema registration/evolution, and workload management.

  • Working knowledge of message queuing, stream processing, and highly scalable big data data

stores.

  • Experience supporting and working with cross-functional teams in a dynamic environment.
  • Have a few weekend side projects up on GitHub.
  • Have contributed to an open-source project.
  • Have worked at a product company.
  • Have a working knowledge of a backend programming language.

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