What you'll do:

• 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 pipelines
• Lead the India engineering team in technical excellence and ownership of critical modules; own the development of new modules and features
• Troubleshoot 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 supervision
• Follow Agile methodology, JIRA for work planning, issue management/tracking

What makes you a great fit:

• 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 tools like 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 bottlenecks
• Take 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.
• 7+ 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.