Hadoop Data Engineer

Overview:

We are looking for a Data Engineer with strong background in PySpark/Big Data development and Hadoop, with a minimum of 5 years of relevant experience in Big Data alone and Total 7+ Years of Exp. Proficiency in Hadoop, Hive, Spark, Unix, scala, SQL and Python.

Roles and Responsibilities:

• Develop, implement, and design data pipelines and ETL processes to efficiently ingest, transform, and load large volumes of data.
• Collaborate with cross-functional teams to gain insights into data requirements and devise scalable solutions for data storage, processing, and retrieval.
• Fine-tune and optimize data processes to ensure exceptional performance, reliability, and data integrity.
• Utilize PySpark, Spark, Hadoop, to build robust data solutions.
• Keep abreast of the latest industry best practices and emerging technologies in data engineering.
• Address and troubleshoot issues related to data pipelines and processing.
• Participate actively in code reviews and offer constructive feedback to enhance code quality.

Qualifications:

• Strong experience with Hadoop and its ecosystem tools such as Spark, Kafka, Hive, and Sqoop
• Proficiency in SQL for data analysis, querying, and performance optimization
• Hands-on experience with Unix/Linux environments
• Programming experience in Scala and Python for data processing and pipeline development
• Experience working with large-scale datasets and distributed data processing frameworks
• Good understanding of ETL processes, data pipelines, and big data architecture

Location

Irvine, United States

Salary

$80 - $88 /hour

Job Type

Contract

Date Posted

March 10th, 2026