Lead Data Engineer

Overview

Exp: 6+ Years

Location: Noida (WFO)

Timings: Mon-Fri; 10:30 AM - 7:30 PM

About The Role

We are looking for an experienced Lead Data Engineer with strong technical expertise and proven leadership capabilities. The ideal candidate has 6+ years of experience in building large-scale data systems, is proficient in Python, SQL, PySpark, and Databricks, and has hands-on experience working with AWS or Azure cloud environments. This role involves leading a team of data engineers while driving architecture, best practices, and scalable data solutions.

Key Responsibilities

• Lead and mentor a team of data engineers to deliver end-to-end data solutions.
• Design, develop, and maintain ETL/ELT pipelines for ingestion, transformation, and analytics.
• Architect and manage scalable data lake and data warehouse environments.
• Build and optimize distributed data processing workflows using PySpark and Databricks.
• Collaborate with analytics, product, and data science teams to understand requirements.
• Define and implement best practices for coding standards, CI/CD, and data governance.
• Establish data quality checks and monitoring frameworks to ensure reliability.
• Troubleshoot performance bottlenecks and provide technical leadership across projects.
• Evaluate new tools and technologies to strengthen the organization’s data capabilities.
  
  

• 6+ years of professional experience in data engineering.
• Strong skills in Python, SQL, PySpark, and Databricks.
• Hands-on experience with cloud platforms such as AWS or Azure.
• Proven experience leading or mentoring a data engineering team.
• Strong understanding of distributed computing principles.
• Experience in building scalable ETL/ELT pipelines.
• Knowledge of CI/CD processes and version control using Git.
• Experience with data modeling and data warehousing concepts.
  
  

• Certifications from Databricks, Snowflake, AWS, or Azure.
• Experience with orchestration tools such as Airflow, ADF, or Prefect.
• Familiarity with delta architecture and modern data stack tools.
• Experience working in Agile environments.