Big Data Developer

Job Summary

We are looking for a highly skilled Senior Spark Engineer with 5–7+ years of hands-on experience in big data development. The role requires strong expertise in Spark (batch and streaming), PySpark, Hadoop, Hive, Kafka, and ETL processes, with proficiency in Java/Scala/Python and data engineering on cloud environments.

Job Roles & Responsibilities

• Develop and deploy Spark-based batch and streaming pipelines
• Work with HDFS, Hive, Kafka, PySpark, and cloud platforms
• Migrate ETL workflows to Spark
• Collaborate with data engineering and analytics teams
• Automate workflows using Airflow or similar tools
• Ensure data quality, performance, and reliability

Cultural Expectations

• Spark (batch + streaming), PySpark
• Java / Scala / Python (any one)
• Hadoop ecosystem: HDFS, Hive
• SQL and ETL knowledge
• Kafka, DataBricks, Airflow
• Experience with cloud-based data platforms
• Jupyter/Developer tools for data processing

Hiring Process

• Live coding task to evaluate coding proficiency.
• Technical interview with senior member from the technical team.
• Final interview with Tech Lead/CTO.