To be successful in this role, you should possess :
- Collaborate closely with Product Management and Engineering leadership to devise and build the right solution.
- Participate in Design discussions and brainstorming sessions to select, integrate, and maintain Big Data tools
and frameworks required to solve Big Data problems at scale.
Design and implement systems to cleanse, process, and analyze large data sets using distributed processing toolslike Akka and Spark.
Understanding and critically reviewing existing data pipelines, and coming up with ideas in collaboration with Technical Leaders and Architects to improve upon current bottlenecksTake initiatives, and show the drive to pick up new stuff proactively, and work as a Senior Individual contributor on the multiple products and features we have.3+ years of experience in developing highly scalable Big Data pipelines.In-depth understanding of the Big Data ecosystem including processing frameworks like Spark, Akka, Storm,and Hadoop, and the file types they deal with.Experience with ETL and Data pipeline tools like Apache NiFi, Airflow etc.Excellent coding skills in Java or Scala, including the understanding to apply appropriate Design Patterns when required.Experience with Git and build tools like Gradle / Maven / SBT.Strong understanding of object-oriented design, data structures, algorithms, profiling, and optimization.Have elegant, readable, maintainable and extensible code style.You are someone who would easily be able to :
Work closely with the US and India engineering teams to help build the Java / Scala based data pipelinesLead the India engineering team in technical excellence and ownership of critical modules; own the development of new modules and featuresTroubleshoot live production server issues.Handle client coordination and be able to work as a part of a team, be able to contribute independently and drive the team to exceptional contributions with minimal team supervisionFollow Agile methodology, JIRA for work planning, issue management / tracking(ref : hirist.tech)