Company Name: VARITE India Private Limited

About The Client:

Client is a pioneering Software Engineering and IT consultancy company, transforming and executing at the intersection of Domain and Technology to create digital leaders for our people, clients, partners, and communities.

About The Job:
- Primary Skill: Data Engineer
- Experience: 5–7 Years
- We are looking for an experienced Data Engineer to design, develop, and maintain scalable cloud-based data platforms and data pipelines.
- The ideal candidate will have solid hands-on experience with PySpark, AWS Glue, Amazon Redshift, and data pipeline orchestration, along with a solid understanding of modern data engineering practices.
- The candidate will work closely with business, analytics, and technology teams to build reliable, scalable, and high-performance data solutions on AWS.

Essential Job Functions:
- Design, develop, and maintain scalable data pipelines and cloud data platforms.
- Develop data transformation and processing solutions using PySpark.
- Build and maintain ETL/ELT workflows using AWS Glue.
- Design,



optimize, and manage data workloads in Amazon Redshift.
- Implement and manage data pipeline orchestration, scheduling, monitoring, and dependency management.
- Perform data ingestion, transformation, cleansing, validation, and integration across multiple data sources.
- Optimize data processing jobs and queries for performance, scalability, and cost efficiency.
- Implement data quality checks, error handling, logging, and monitoring mechanisms.
- Troubleshoot pipeline failures and production data issues and ensure timely resolution.
- Collaborate with data architects, analysts, application teams, and other stakeholders to understand data requirements.
- Follow best practices for data security, governance, reliability, and operational support.
- Contribute to the continuous improvement and automation of data engineering processes.

Qualifications:
- 5–7 years of hands-on experience in Data E

📌 Data Engineering (Chennai)
🏢 VARITE
📍 Chennai