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Lead Snowflake Data Engineer

RANDOMTREESβ€’Anywhere in India/Multiple Locations, Remote
SENIOR_LEVELLead
πŸ‘οΈ 0 viewsβ€’πŸ“ 0 applicationsβ€’Posted 10/24/2026β€’Expires 11/25/2026
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Job Description

Role Overview : We are looking for a Lead Snowflake Data Engineer to lead the design, development, and optimization of enterprise-scale data pipelines and cloud data warehouse solutions. The role requires deep expertise in Snowflake, dbt, SQL, and data engineering, along with the ability to drive technical decisions, establish best practices, and guide engineering teams. Responsibilities : - Lead the design and implementation of scalable, reliable, and high-performance data pipelines using Snowflake. - Define data engineering standards, architecture, and best practices for ETL/ELT development and data transformation. - Oversee dbt implementations, including reusable data models, transformation logic, testing, and maintainability. - Drive data modeling, warehouse design, and SQL performance optimization. - Design and manage workflow orchestration using Apache Airflow. - Guide the development of data solutions using Python and/or PySpark. - Identify and resolve complex data pipeline, integration, and performance issues. - Ensure data quality, reliability, scalability, and efficient warehouse resource utilization. - Collaborate with stakeholders to translate business requirements into technical solutions. - Mentor engineers, review code and data models, and drive continuous improvement in engineering practices. - Take ownership of technical delivery, implementation decisions, and overall solution quality. Requirements : - 10 - 15 years of experience in data engineering, data warehousing, or related fields. - Extensive hands-on experience with Snowflake, advanced SQL, and performance optimization. - Strong experience with dbt and large-scale data transformation workflows. - Deep understanding of ETL/ELT architecture, data modeling, and cloud data warehousing. - Experience with Apache Airflow or similar orchestration tools. - Proficiency in Python and/or PySpark. - Proven experience designing and optimizing complex, scalable data pipelines. - Experience providing technical leadership, mentoring engineers, and reviewing code. - Strong problem-solving, communication, and stakeholder-management skills.

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