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Atomic North
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Big Data Specialist

Big Data Specialist

Atomic North

8 years

0 Lacs

pune maharashtra india

Posted:2 days ago| Platform:

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Skills Required

data pyspark reliability design hive sqoop hadoop sql tuning optimization agile schedule apache airflow resolve engineering collaborative workflow orchestration communication devops spark

Work Mode

On-site

Job Type

Full Time

Job Description

Big Data Engineer

Location: Pune/Nagpur (WFO)

Experience Required: 8+ Years

Long term onsite to Abu Dhabi

Job Summary

We are looking for an experienced Big Data Engineer with strong expertise in PySpark and Big Data ecosystems.
The ideal candidate will be responsible for designing, developing, and optimizing scalable data pipelines while ensuring high performance and reliability.

Key Responsibilities:

• Design, develop, and maintain data pipelines using PySpark and related Big Data technologies.

• Work with HDFS, Hive, Sqoop, and other tools in the Hadoop ecosystem.

• Write efficient HiveQL and SQL queries to handle large-scale datasets.

• Perform performance tuning and optimization of distributed data systems.

• Collaborate with cross-functional teams in an Agile environment to deliver high-quality solutions. • Manage and schedule workflows using Apache Airflow or Oozie.

• Troubleshoot and resolve issues in data pipelines to ensure reliability and accuracy.

Required Skills

• Proven experience in Big Data Engineering with a focus on PySpark.

• Strong knowledge of HDFS, Hive, Sqoop, and related tools.

• Proficiency in SQL/HiveQL for large datasets.

• Expertise in performance tuning and optimization of distributed systems.

• Familiarity with Agile methodology and collaborative team practices.

• Experience with workflow orchestration tools (Airflow/Oozie).

• Strong problem-solving, analytical, and communication skills.

Good to Have:

• Knowledge of data modeling and data warehousing concepts.

• Exposure to DevOps practices and CI/CD pipelines for data engineering.

• Experience with other Big Data frameworks such as Spark Streaming or Kafka.

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