Description

Build and maintain scalable data pipelines and ETL workflows using Hadoop ecosystem components.

This role is hybrid.

Responsibilities

• Develop and optimize Spark and Hive SQL queries for large-scale data processing.
• Design and implement Oozie workflows for scheduling, data transformation, and replication.
• Build data ingestion and wrangling solutions using Kafka, Sqoop, Alteryx, or standard ETL tools.
• Collaborate with business stakeholders to define requirements and deliver data solutions in an agile environment.

Required Skills

• 7+ years of experience with Hadoop development, including Hive, HBase, and MapReduce.
• Strong proficiency in Python and Scala for data engineering tasks.
• Hands-on experience with Spark optimization and Hive SQL tuning.
• Experience with data replication tools such as Kafka, Sqoop, or Alteryx.
• Solid background in SQL, with experience in Teradata, Oracle, or DB2 preferred.
• BS in Computer Science or related field, or equivalent professional experience.
• Proven ability to work independently and communicate effectively with business customers.

Preferred Skills

• Experience with Google Cloud Platform (GCP).
• Proficiency in Shell or Perl scripting.
• Experience with visualization tools like QlikView or Java development.

Key Skills

Education

Any Graduate