Big Data Engineer
Live Connections
2 - 5 years
Hyderabad
Posted: 03/05/2026
Job Description
Job Title: Big Data Developer (On-Premises)
Location: Hyderabad
Experience: 5 to 7 years
Employment Type: Full-Time
Required Notice Period: Immediate Joiners or Serving Notice or 30 days
Job Overview
We are seeking a skilled Big Data Developer with strong hands-on experience in on-premises data ecosystems. The ideal candidate should have deep expertise in Hadoop-based technologies and a solid foundation in distributed data processing, performance optimization, and programming.
Key Responsibilities
- Design, develop, and maintain scalable Big Data solutions using on-premises technologies
- Work extensively with Hadoop ecosystem components including HDFS and Spark
- Write and optimize complex SQL queries for large-scale data processing
- Perform performance tuning and optimization in Hive and Spark environments
- Develop and maintain data pipelines using Shell scripting and Python
- Collaborate with cross-functional teams to deliver high-quality data solutions
Required Skills & Expertise
Big Data Technologies
- Strong knowledge of Hadoop ecosystem, including HDFS and Spark architecture
SQL & Performance Optimization
- Advanced SQL skills with mandatory experience in performance tuning for:
- Hive
- Spark
Programming & Scripting
- Proficiency in:
- Shell Scripting
- Python (Core Python & PySpark)
- Good to have: Scala
Mandatory Requirements
- Candidates must have recent and strong hands-on experience in on-premises Big Data technologies
- At least 80% of project work should reflect usage of the above-mentioned tech stack
Important Note
- Do not consider candidates who:
- Are not currently hands-on with on-prem Big Data technologies
- Have experience limited only to Cloud platforms (e.g., Azure Data Engineering)
How to Apply
If you meet the above criteria and are interested in this opportunity, please share your updated resume at:
Email: abhishek.m@livecjobs.com
WhatsApp / Contact: 9154908075
We look forward to connecting with you!
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