Job Requirements

• Proficient in Functional Java or Scala, Databricks, and Data Modeling.
• Knowledge of AWS Big Data/Analytics (S3, EMR, Glue, Redshift, QuickSight, Kinesis).
• Experience with data storage (Hadoop HDFS, S3, Kafka) and big data tech stacks (Hadoop, Spark, Cassandra, MongoDB).
• In-depth knowledge of the Hadoop ecosystem (HDFS, Spark, Kafka, etc.) and IaaS/PaaS solutions (AWS).
• Familiar with network protocols, relational/non-relational databases, and mocking frameworks (Mockito, ScalaTest).
• Skilled in PySpark/Spark with Scala, code versioning (Git), and Agile practices (TDD, CI).
• Collaborate with cross-functional teams to design efficient, data-driven solutions.

Job Responsibilities

• Design, develop, and maintain scalable data services and pipelines for large data ingestion, storage, and management.
• Architect highly scalable, low-latency systems and enhance existing ones while addressing technical debt.
• Mentor developers, contribute to code quality, and ensure robust, scalable software development.
• Collaborate with stakeholders and support integrations, participating in sprint planning and occasional out-of-hours support.
• Proactively advise on best practices and build necessary tools (e.g., SBT, Gradle, Maven).

Perks

• Object Bootcamp
• Sabbatical Leaves
• Parental Leaves
• Office Perks (Free Meal, Snacks)
• Career Oriented Work

Culture

• Open Culture
• Flat Hierarchy
• 360-degree feedback
• Mentorship Program
• People Supportive
• Competitive & Friendly Environment