Data Engineer

• Design, develop, and maintain ETL pipelines and data workflows using Spark, Hadoop, Hive, and related frameworks.
• Work with large-scale structured and unstructured data to enable business insights.
• Collaborate with Data Scientists, Analysts, and other stakeholders to ensure data availability and quality.
• Implement data ingestion and transformation processes using distributed computing frameworks.
• Optimize performance of big data applications and troubleshoot issues in the data pipelines.
• Ensure data security, compliance, and governance across all platforms.

Requirements

• 3–6 years of experience as a Data Engineer or in a similar role.
• Strong hands-on knowledge of Apache Spark, Hadoop, Hive, HDFS, and SQL.
• Proficiency in Python / Scala / Java for data engineering tasks.
• Solid understanding of data warehousing concepts, ETL design patterns, and data modeling.
• Experience with workflow orchestration tools (Airflow, Oozie, etc.) is a plus.
• Familiarity with cloud platforms (Azure, AWS, or GCP) is advantageous.
• Strong problem-solving skills and ability to work in a collaborative team environment.