DATA ENGINEERING LEAD

Vrinda International; New Delhi; On-site; INR 3,000,000 - 6,000,000; Full time

Job summary

Vrinda International in New Delhi leads IT talent solutions across global markets. The Data Engineering Lead will architect robust data pipelines, drive data strategy, and mentor a high-performing team within the IT services domain.

You will design scalable data models, optimize ETL/ELT processes, monitor pipelines, and collaborate with stakeholders to align data solutions with business goals. The role requires strong Python/SQL skills and the ability to balance technical depth with stakeholder

Qualifications

• 8–12 years of data engineering or related technical field experience.
• Proficient in SQL and Python for data manipulation and development.
• Strong data modeling techniques and data optimization.
• Experience building and maintaining ETL/ELT workflows and data integration.
• Ability to monitor complex data pipelines and troubleshoot effectively.
• Excellent stakeholder management and cross-team collaboration.

Responsibilities

• Design data architecture strategies to support analytics and operational needs.
• Develop and maintain ETL/ELT pipelines for diverse systems.
• Construct and refine data models for performance and reliability.
• Establish monitoring protocols for data pipelines and minimize downtime.
• Mentor team members, conduct code reviews, promote technical excellence.
• Collaborate with cross-functional teams to align data solutions with business goals.

Skills

SQL

Python

Data modeling

ETL/ELT

Stakeholder mgmt

Team leadership

Tools

Airflow

Spark

Hadoop

Job description

New Delhi–NCR, India | Posted on 10/16/2026

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Job Description

Summary

The Data Engineering Lead serves as a pivotal figure within the IT Services sector, responsible for architecting and overseeing the creation of robust, large-scale data pipelines. This role demands a strategic vision to drive data architecture and engineering initiatives while ensuring seamless data integration and optimization. The position is critical for enabling data-driven decision-making across the organization, requiring a professional who can balance technical depth with the ability to manage complex stakeholder relationships and mentor a high-performing team.

Responsibilities

• Design and implement comprehensive data architecture strategies to support enterprise-wide analytics and operational needs.
  
• Develop and maintain efficient ETL/ELT processes to facilitate smooth data integration across diverse systems.
  
• Construct and refine data models to ensure high performance, scalability, and reliability of data assets.
  
• Establish rigorous monitoring protocols for data pipelines, proactively identifying and resolving troubleshooting issues to minimize downtime.
  
• Lead team members through mentorship, conduct thorough code reviews, and foster a culture of technical excellence.
  
• Manage stakeholder expectations and collaborate with cross-functional teams to align data solutions with business objectives.
  
• Oversee the deployment and optimization of large-scale data pipelines to handle increasing data volumes effectively.
  

Requirements

Requirements:

• A minimum of 8 to 12 years of professional experience in data engineering or related technical fields.
  
• Proven expertise in SQL and Python for data manipulation, scripting, and application development.
  
• Deep understanding of data modeling techniques and strategies for data optimization.
  
• Strong background in building, deploying, and managing ETL/ELT workflows and data integration solutions.
  
• Demonstrated ability to monitor complex data pipelines and execute effective troubleshooting procedures.
  
• Exceptional stakeholder management skills with a track record of successful cross-departmental collaboration.
  
• Experience in leading teams, providing technical guidance, and conducting peer code reviews.
  
• Familiarity with the design and implementation of large-scale data infrastructure.