Responsibilities :

Design, develop, and support scalable data processing workflows using Hadoop and PySpark for batch and large-volume processing.

Build and maintain data pipelines that ingest, transform, and validate data from multiple sources into curated datasets.

Optimize Spark jobs for performance (partitioning, caching, shuffle tuning) and improve overall pipeline efficiency and reliability.

Perform data quality checks, reconciliation, and root-cause analysis for pipeline failures or data anomalies.

Collaborate with cross-functional teams to understand requirements, translate them into technical solutions, and deliver within timelines.

Create clear technical documentation for workflows, data mappings, and operational runbooks.

Participate in code reviews, follow engineering best practices, and contribute to continuous improvement of standards and tooling.

Additional Responsibilities:

2-5 years of experience in big data engineering or data processing roles.

Bachelor's/Master's degree in Engineering, Computer Science, or equivalent (BTech/BE/MCA/MSc/MTech or related).

Hands-on experience with Hadoop ecosystem concepts (HDFS, distributed processing fundamentals).

Practical experience developing data transformations using PySpark.

Strong problem-solving skills with the ability to debug data and job execution issues in distributed environments. Preferred Qualifications:

Experience building end-to-end ETL/ELT pipelines and managing dependencies across multiple data workflows.

Working knowledge of Spark optimization techniques and handling skewed/large datasets efficiently.

Familiarity with data modeling concepts and designing curated datasets for analytics and reporting use cases.

Exposure to production support practices such as monitoring, incident triage, and improving pipeline resiliency.

Strong communication skills to collaborate effectively with stakeholders and explain technical trade-offs clearly. Good to have skills: Hive, HBase, Kafka, Airflow, Scala

Technical and Professional Requirements:

echnology- Big Data - Data Processing- PySpark,Technology- Big Data - Hadoop- Hadoop Administration- Hadoop

Hadoop / PySpark

Hadoop / PySpark