Senior Data Engineer

Kazhuga is hiring Data Engineers with strong hands-on experience in Hadoop and PySpark to work on enterprise-scale data engineering and cloud modernization initiatives.

Important**

Please apply ONLY if you have hands-on project experience in:

• Hadoop Ecosystem
• PySpark / Apache Spark
• On-Premise to Cloud Migration

Candidates without the above experience will not be considered.

Responsibilities

• Develop and optimize ETL/ELT pipelines using PySpark and Spark.
• Design and maintain large-scale data processing solutions on Hadoop.
• Participate in on-premise to cloud migration projects.
• Build scalable data ingestion and transformation pipelines.
• Optimize data processing performance and troubleshoot production issues.
• Collaborate with architects and cross-functional engineering teams.

Mandatory Skills

• 4-6 years of Data Engineering experience
• Hadoop (Mandatory)
• PySpark / Apache Spark (Mandatory)
• Python
• SQL
• ETL/Data Pipelines
• Linux & Git

Preferred Skills

• AWS / Azure / GCP
• Apache Airflow
• Kafka
• Apache Iceberg
• Databricks or Snowflake
• Docker / Kubernetes

Preferred Candidate Profile

We are looking for candidates who have:

• 4-6 years of relevant Data Engineering experience.
• Hands-on experience with Hadoop and PySpark in production environments.
• Experience working on On-Premise to Cloud Migration projects.
• Strong SQL and Python skills.
• Excellent analytical and problem-solving abilities.

Do NOT apply if

• Your experience is primarily in BI, Data Analytics, Power BI, Tableau, SQL Developer, Database Administration, Testing, Java Development, or generic Software Development without Hadoop & PySpark experience.
• You do not have hands-on Hadoop project experience.