Data Engineer_105493

Company:IT Services Organization

Key Skills: Databricks, Apache Spark, Hadoop, Azure, Python, AWS, Airflow, Snowflake, Pyspark, Kafka, SQL

Roles and Responsibilities:

• Design, develop, and maintain scalable batch and distributed data processing pipelines using Python, Apache Spark, Hadoop, and Databricks.
• Build and operate data engineering solutions across AWS and Microsoft Azure cloud environments.
• Develop data ingestion, transformation, validation, and integration workflows for large and varied datasets.
• Troubleshoot data pipeline failures, identify performance bottlenecks, and improve reliability of production workloads.
• Implement data quality checks, operational documentation, and engineering standards for maintainable data platforms.

Skills Required:

• 5-9 years of relevant data engineering experience; candidates available to join immediately or within 30 days are preferred.
• Hands-on experience with AWS and Microsoft Azure data engineering environments.
• Strong programming ability in Python and practical experience with Apache Spark and Hadoop.
• Experience building scalable data pipelines and distributed processing solutions using Databricks.
• Understanding of data architecture, storage, transformation, integration, and production support practices.

Good to Have:

• Experience with SQL, Apache Kafka, Apache Airflow, PySpark, or Snowflake.

Education: B.Tech or M.Tech in Computer Science, Information Technology, Engineering, or a related discipline.