Chiselon Technologies Private Limited

Big Data Developer

Chennai, TN, IN

8 days ago
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Summary

We are hiring for one of our client!!!


Position - Big Data Engineer

Experience - 5+years

Location - Chennai, Bangalore

Work Mode - Hybrid

Notice Period - Immediate Joiners(Seving Notice Period within 15days only)



Job Overview

We are seeking a skilled Big Data Developer to join our team in a mid-level position. This full-time, hybrid role is based in Chennai and Bangalore. The ideal candidate will have 4 to 6 years of experience in big data technologies, contributing to developing and optimizing high-quality data pipelines and applications.


Qualifications and Skills

Proficiency in Java (Mandatory skill) is essential for developing robust and scalable data processing applications.

Expertise in Python (Mandatory skill) for efficient data manipulation and automation of data processing tasks.

In-depth knowledge of ETL (Mandatory skill) processes to extract, transform, and load data from various sources into centralized databases.

Experienced in working with Hadoop ecosystems, leveraging distributed computing for processing large datasets efficiently.

Proficient in utilizing Hive for executing queries and managing large datasets in a Hadoop environment.

Skilled in PySpark for real-time data processing and analytics, optimizing data workflows within a big data framework.

Strong command over SQL for database querying, involving complex joins, aggregations, and performance tuning.

Problem-solving and analytical skills to troubleshoot data issues and enhance data architectures.


Roles and Responsibilities

Design and implement scalable data pipelines for batch and stream processing to handle large datasets efficiently.

Collaborate with data scientists and architects to integrate analytics and reporting solutions.

Optimize ETL processes to ensure data accuracy and integrity across various platforms.

Develop and maintain data workflows using Hadoop and related technologies to support data projects.

Enhance data models and data architecture to improve data quality and accessibility.

Identify and resolve data discrepancies and implement enhancements to improve system performance.

Stay updated with the latest big data technologies and incorporate them into current systems when beneficial.

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