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Medium competition due to metro location and popular data engineering title offset by seniority and platform-specific requirements.
High because Azure, Snowflake, and DBT expertise creates strong domain-specific hiring bias.
High due to mandatory 8+ years and specific Azure Data Factory, Snowflake, and DBT expertise.
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Design and develop ETL/ELT data pipelines using Azure Data Factory, Snowflake, and DBT.
Build, monitor, troubleshoot, and optimize data integration workflows and pipelines from various sources to Snowflake.
Collaborate with stakeholders and cross-functional teams to translate business requirements into technical solutions while maintaining data quality and governance.
8+ years of experience in data engineering roles using Azure and Snowflake.
Bachelor’s or master’s degree in Computer Science, Data Engineering, Information Systems, or a related field.
Strong experience with Azure Cloud Platform services, Azure Data Factory, Snowflake, DBT, and proficiency in SQL.
Location requirement: Gurugram with Hybrid work mode.
Experienced in designing scalable and optimized cloud-native data pipelines operating in Azure environments.
Skilled at translating complex business requirements into technical implementations with attention to data governance.
Proven ability to collaborate effectively with analysts, architects, and DevOps teams in large-scale data environments.