Hadoop Developer

@ Neshent Technologies
Neshent Technologiesneshenttechnologies.com

Hadoop Developer

Cockrell Hill, Texas
Posted 1 week ago

About the job

The company specializes in data solutions, focusing on designing and maintaining scalable Big Data systems. The role involves developing and supporting data pipelines, ETL processes, and optimizing performance in a production environment.

Requirements

  • 4+ years Big Data experience
  • Hadoop/Cloudera, Spark expertise
  • Python, SQL, Unix scripting
  • ETL, data ingestion, transformation
  • SQL query optimization

Qualifications

  • Strong analytical and problem-solving skills
  • Experience supporting production data apps
  • Understanding of distributed systems
  • Familiarity with Agile practices
  • Financial services experience preferred

Full job description

We are looking for a Senior Hadoop Developer with strong experience in Big Data, Hadoop/Cloudera, Spark, Python, SQL, and ETL to design, develop, and support scalable data solutions in a production environment.

Roles and Requirements
  • 4+ years of experience in Big Data and data warehousing.
  • Strong hands-on experience with Hadoop/Cloudera, HDFS, Hive, and Spark/PySpark.
  • Proficiency in Python, Scala, SQL, and Unix/Shell scripting.
  • Strong experience in ETL, data ingestion, transformation, and integration.
  • Experience with complex SQL query optimization and performance tuning.
  • Experience with AutoSys or similar enterprise scheduling tools.
  • Strong understanding of distributed systems and large-scale data processing.
  • Experience supporting production Big Data applications and troubleshooting critical issues.
  • Understanding of Agile methodologies and enterprise development/operational processes.
  • Strong analytical, problem-solving, communication, and collaboration skills.
  • Experience designing analytical/data warehouse environments and BI solutions.
  • Financial services/banking experience preferred.
Primary Responsibilities
  • Develop and maintain scalable Hadoop/Spark-based data pipelines.
  • Support data ingestion from multiple source systems.
  • Develop ETL and data transformation solutions using Hive, Spark, Python, and SQL.
  • Optimize SQL queries and Big Data jobs for performance.
  • Troubleshoot production issues and perform root-cause analysis.
  • Support scheduling, monitoring, and operational processes.
  • Collaborate with architects, developers, analysts, and business teams.
  • Evaluate and adopt emerging Big Data technologies where appropriate.
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