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Job Description & How to Apply Below
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.
Required Skills & Experience
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.
Preferred Qualifications
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.
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