Description

Design, build, and maintain scalable Big Data pipelines and distributed processing systems for large-scale applications.

This role is on-site.

Responsibilities

• Design and develop distributed data processing applications using modern frameworks.
• Build and optimize backend services and APIs for data platforms.
• Maintain end-to-end data solutions, ensuring quality, scalability, and reliability.
• Troubleshoot performance issues in large-scale data systems.
• Collaborate with cross-functional teams to deliver complete data solutions.

Required Skills

• 8+ years of software development experience, preferably in distributed data systems.
• 5+ years of hands-on experience designing Big Data solutions.
• Strong proficiency in Apache Spark (mandatory).
• Experience with Hadoop ecosystem components (HDFS, Hive, Impala, HBase).
• Programming proficiency in Java, Scala, or Python.
• Expert-level SQL skills, including query building, debugging, and optimization.
• Experience with data formats: XML, JSON, Parquet, Avro, Protobuf.
• Backend development experience with Spring Boot or Microservices architecture.
• Hands-on experience with Apache Kafka for real-time data pipelines.

Preferred Skills

• Experience with Databricks Lakehouse Platform (Delta Lake, Workflows, Unity Catalog, MLflow).
• Familiarity with AI productivity tools like GitHub Copilot or ChatGPT for development efficiency.

Key Skills

Education

Any Graduate