Hadoop Data Engineer

Technology

Bengaluru

About the job

The purpose of this role is to maintain, improve, clean and manipulate data in the business’s operational and analytics databases. The Data Engineer works with the business’s software engineers, data analytics teams, data scientists and data warehouse engineers in order to understand and aid in the implementation of database requirements, analyse performance, and troubleshoot any existent issues.

Responsibilities:

• Design, develop, and maintain scalable data pipelines and systems for data processing.

• Utilize Hadoop and related technologies to manage large-scale data processing.

• Perform data ingestion using Kafka & spark, Sqoop and various file formats and process data into Hive using Beeline/spark.

• Develop and maintain shell scripts for automation of data processing tasks

.• Implement full and incremental data loading strategies to ensure data consistency and availability.

• Orchestrate and monitor workflows using Apache Airflow. • Ensure code quality and version control using Git.

• Troubleshoot and resolve data-related issues in a timely manner.

• Stay up to date with the latest industry trends and technologies to continuously improve our data infrastructure.

Requirements:

• Proficiency in SQL and Hive (Essential).

• Proven experience as a Data Engineer (ETL, data warehousing) (Essential).

• Strong knowledge of Hadoop and its ecosystem (HDFS, YARN, MapReduce, Tez and spark).

• Expertise in full and incremental data loading techniques.

Good to have:

• Understanding of PySpark and its application in real-time data processing.

• Hands-on experience with Apache Airflow for workflow orchestration.

• Proficiency with Git for version control

• Experience on Postgres SQL or SQL server or MSBI.

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