Java developer with Hadoop

Primary Skill: PySpark, Hive, Python, SQL

Secondary: Unix, Kafka, Java

Experience: 10+ years

We are seeking a highly experienced Hadoop Spark Developer with 10+ years of expertise in Big Data technologies, including PySpark, Hadoop Ecosystem, Hive, and Python. The ideal candidate will be responsible for designing, developing, optimizing, and maintaining large-scale data processing solutions.

Experience with Microsoft Copilot for AI-assisted development and productivity enhancement is highly desirable. The developer should hold a bachelor's or master's degree.

The candidate should possess strong analytical skills, hands-on experience in distributed data processing, and the ability to work closely with business stakeholders, architects, and data engineering teams.

Design, develop, and maintain scalable Big Data solutions using Hadoop and Spark.

Build and optimize ETL/ELT pipelines using PySpark, Hive, and Python.

Process and analyze large datasets in distributed environments.

Develop high-performance Spark jobs and optimize existing workloads.

Create and manage Hive tables, partitions, views, and complex queries.

Implement data quality, data validation, and reconciliation frameworks.

Perform code reviews and ensure adherence to coding standards and best practices.

Utilize Microsoft Copilot to accelerate development, automate code generation, troubleshooting, documentation, and testing activities.

Strong experience building both batch and real-time streaming applications with Kafka.

Collaborate with Data Architects, Data Scientists, Business Analysts, and DevOps teams.

Troubleshoot production issues and perform root cause analysis.

Design data ingestion frameworks for structured, semi-structured, and unstructured data.

Participate in Agile ceremonies including sprint planning, estimation, and retrospectives.

Mentor junior developers and provide technical leadership.