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.

Valuable 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.

📌 Data Engineer (Jaipur)
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