Data Engineer

Key Responsibilities:

• Design, implement, and optimizedata pipelinesfor large-scale data processing.
• Develop and maintain ETL/ELT workflows usingSpark,Hadoop,Hive, andAirflow.
• Collaborate with data scientists, analysts, and engineers to ensure data availability and quality.
• Write efficient and optimizedSQLqueries for data extraction, transformation, and analysis.
• LeveragePySparkand cloud tools (preferablyGoogle Cloud Platform) to build reliable and scalable solutions.
• Monitor and troubleshoot data pipeline performance and reliability issues.

Required Skills:

• 46 years of experience in aData Engineeringrole.
• Strong hands-on experience withPySparkandSQL.
• Good working knowledge ofGCPor any major cloud platform (AWS, Azure).
• Experience withHadoop,Hive, anddistributed data systems.
• Proficiency in data orchestration tools such asApache Airflow.
• Ability to work independently in a fast-paced, agile environment.

Good to Have:

• Experience with data modeling and data warehousing concepts.
• Exposure to DevOps and CI/CD practices for data pipelines.
• Familiarity with other programming/scripting languages (Python, Shell scripting).

Educational Qualification:

• Bachelors or Master's degree in Computer Science, Information Technology, Engineering, or a related field.