Job Summary
We are looking for an experienced Big Data Developer with robust expertise in Hadoop ecosystem, Spark, Scala, and SQL to design and build scalable data processing systems. The ideal candidate should have hands-on experience working with large datasets, distributed computing, and modern data architectures.

Key Responsibilities
Design, develop, and maintain big data pipelines using Hadoop and Spark
Build scalable data processing frameworks using Scala and Spark
Develop and optimize Hive queries and SQL scripts for large datasets
Work with distributed storage systems like HDFS
Perform data ingestion, transformation, and processing (ETL/ELT)
Optimize performance of Spark jobs and Hadoop workloads
Collaborate with data engineers, analysts, and business teams
Ensure data quality, reliability, and scalability
Troubleshoot and resolve performance bottlenecks
Required Skills (Must-Have)




Strong hands-on experience with:
Hadoop ecosystem (HDFS, Hive, YARN)
Apache Spark (Core, SQL, DataFrames)
Scala programming
Advanced SQL
Experience in big data processing and distributed systems
Knowledge of data warehousing concepts
Strong problem-solving and debugging skills
Good-to-Have Skills
Experience with Apache Kafka / streaming frameworks
Exposure to cloud platforms (AWS / Azure / GCP)
Familiarity with Airflow or workflow orchestration tools
Knowledge of Python / PySpark
Understanding of data lake architectures
Qualifications

- Bachelor's or Master's degree in Computer Science, Engineering, or related field
- 5–8 years of relevant experience in Big Data technologies

Skills: hadoop,big data,spark,sql,scala

📌 AWS Big data Engineer (Pune)
🏢 Zorba AI
📍 Pune