Apache Spark and Hadoop Developer

4 - 10 years

0 Lacs

Posted:1 week ago| Platform: Foundit logo

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On-site

Job Type

Full Time

Job Description

Greetings from TCS!

Skillset : Apache Spark and Hadoop

Location: Bangalore

Experience Range: 4 - 10 years

Must-have skills

  • Design, build, and maintain scalable big data pipelines for processing and analyzing large datasets using Spark, Airflow, Bodo, Flume, Flink, etc.
  • Utilize technologies like Hadoop, Spark, Kafka, and NoSQL databases.
  • Develop data ingestion, transformation, and aggregation strategies.
  • Design and implement data warehouses and data marts using Presto, Snowflake, or similar technologies.
  • Create efficient data models and schemas for optimal query performance.
  • Great to have an understanding of graph query (GQL), Gremlin, Cypher, etc.
  • Know to build business system-engineering architectures using graphs, how to scale the workload on distributed systems.
  • Hands on experience applying graphs for business impact, including experience on data management, infrastructure, budgeting, trade-offs, project workflow management, and business processes engineering.
  • Strong programming skills: Python/Scala/Rust for Supercomputing on TB+ data.
  • Experience with creating quantitative analytics and business operation dashboards using Tableau, SuperSet or other visualisation tools.
  • Experience with data mining, relational and noSQL databases, and data warehouse for data automation.
  • Experience working with large language model and natural language processing is a plus.
  • Excellent problem solving, critical thinking backed by expert understanding of probability, statistics, algorithms and mathematics.
  • Be able to strategize and innovate business solutions for high impact projects.
  • Be able to evaluate and transform latest, untested academic methods into production workflows.
  • Self-driven, highly motivated and ability to work both independently and within a team.
  • Operate optimally in fast pace development environment with dynamic changes, tight deadlines and limited resources.

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