Data Engineer (Hadoop) - Walk-in Opportunity

Role Overview

The role involves designing, developing, and sustaining scalable data pipelines to efficiently extract, transform, and load data from diverse sources, ensuring smooth data flow and easy accessibility.

Key Responsibilities

• Develop and maintain data pipelines that support seamless data movement and accessibility.
• Work closely with various teams to integrate data from several sources, maintaining data consistency, accuracy, and dependability.
• Enhance data processing workflows and storage solutions focusing on performance, scalability, and cost-effectiveness.
• Establish data quality checks and validation procedures to maintain data accuracy and completeness throughout its lifecycle.
• Continuously monitor data pipelines and infrastructure to quickly detect and fix issues, ensuring system stability and dependability.

Candidate Profile

• Strong command over programming languages like Python, Java, or Scala for data engineering purposes.
• Experience working with both SQL and NoSQL database systems.
• Practical knowledge of big data platforms including Hadoop, Spark, Kafka, and Hive to manage large datasets and real-time data streams.
• Expertise with data warehousing technologies such as Amazon Redshift, Google BigQuery, and Snowflake.
• Skilled in creating and maintaining ETL processes using solutions like Apache NiFi, Talend, or Informatica.

Additional Information

Eligibility: Individuals holding any graduate degree are welcome to apply.