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SAP Apache Spark Developer 3-6 yrs 
India, Karnataka, Bengaluru 
59182651

02.12.2024

What you’ll do

  • You will work with a team of highly technical and motivated developers.

  • You should be able to collaborate and work with teams spread across geographies and time zones.

  • Collaborate with stakeholders to understand business requirements and translate them into technical solutions.

  • Design and implement scalable and efficient code, following best practices and industry standards.

  • Own your code across every stages of software development lifecycle including ideation, design, development, quality and customer support

  • Build an end-to-end understanding of features across various components.

  • Adhere to the agile engineering practices and processes followed by the team.

  • Create and maintain detailed technical documentation and design specifications.

What you bring

  • 3 - 6 years of overall software development experience in Apache Spark framework

  • In-depth knowledge of Spark Core, Spark SQL and Spark streaming

  • Experience in working with Data Frames, Datasets and RDDs

  • Ability to implement real-time data processing and batch processing workflows

  • Good understanding of Spark architecture including driver and executor interaction

  • Proficiency in writing clean and efficient code in one or more Spark programming languages such as Python/Scala/Java

  • Proficiency in Spark job optimization including partitioning, caching and resource allocation

  • Familiarity with tuning techniques like adjusting executor memory, shuffle partitions, and broadcast joins.

  • Experience building and managing ETL pipelines using Spark.

  • Ability to connect and work with relational databases using JDBC/ODBC

  • Experience deploying Spark jobs on cloud platforms such as AWS, Azure, Google Cloud

  • Proficiency in using monitoring and debugging tools such as Spark UI, Grafana or Promethus

  • Writing and optimizing complex SQL queries and understanding query execution plans and leveraging Spark SQL for distributed query processing.