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Big Data Engineer (Hadoop & Cloudera)

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Onsite

Big Data Engineer (Hadoop & Cloudera)

Sunware Technologies

Big Data Engineer (Hadoop & Cloudera)

Skills

SQL QueriesBig DataData EngineeringPythonPySparkApache AirflowHadoop

3 months ago

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Important information


Contract type:

Permanent

Location:

Pune, Maharashtra, India

Work mode:

Onsite

Published on:

7 August 2026

What they need


Job Title: Data Engineer - Hadoop and Cloudera

Experience: 8+ Years

Location: Pune

Role Summary

We are looking for an experienced Data Engineering Specialist to design, develop, and optimize scalable data ingestion and ETL pipelines across the Hadoop ecosystem. The ideal candidate should have strong hands-on experience with Apache NiFi, Spark/PySpark, Hadoop/HDFS, Apache Airflow, Cloudera Data Engineering (CDE), Hive, SQL, and Python.

Mandatory Skills

  • Apache NiFi
  • Spark/PySpark
  • Hadoop/HDFS
  • Apache Airflow
  • Clouder Data Engineering (CDE)
  • Hive & SQL
  • Python

Key Responsibilities

  • Design, develop, and maintain scalable ETL and data ingestion pipelines.
  • Build and optimize data processing solutions using Spark, PySpark, and NiFi.
  • Develop and manage Airflow workflows for scheduling and orchestration.
  • Work with Hadoop, HDFS, Hive, and CDE for enterprise data processing.
  • Write efficient Hive SQL and Python code for data transformation and automation.
  • Monitor, troubleshoot, and optimize production data pipelines.
  • Collaborate with cross-functional teams to deliver reliable data solutions.

Required Skills

  • 8+ years of experience in Data Engineering and Big Data technologies.
  • Strong expertise in Apache NiFi, Spark/PySpark, Hive, SQL, Python, and Airflow.
  • Good understanding of Hadoop, HDFS, distributed data processing, and ETL best practices.
  • Hands-on experience with Cloudera Data Engineering (CDE) or similar enterprise data platforms.
  • Experience supporting and optimizing production data pipelines.
  • Strong analytical, problem-solving, and communication skills.

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