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Tier-1 brand, metro location, mid-level Snowflake data engineer role attracts high applicant density.
Snowflake, DBT and AWS skills are transferable across industries but require data engineering experience.
Explicit 5–8 years plus SnowPro certification and Snowflake/AWS/DBT requirements create strict shortlisting.
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Design, develop, and optimize data pipelines and data models using Snowflake and DBT workflows.
Implement scalable SQL queries, automate data workflow deployment with CI/CD, and ensure data quality and governance.
Leverage AWS cloud services (Glue, Lambda, Step Functions) and orchestration tools like Apache Airflow for scalable data solutions.
5 to 8 years of professional experience in data engineering or related roles.
Mandatory skills: Snowflake (SnowPro Core certification required), SQL, Data Modeling, Python, AWS Glue, Lambda, and Step Functions.
Bachelor's or Master's degree in Engineering, MBA or MCA with minimum 60% marks.
Experience with DBT workflows, Apache Airflow, and CI/CD tools (e.g., Git, Jenkins, Azure DevOps).
Experienced with modern cloud data platforms, particularly Snowflake and AWS ecosystem, to build scalable data engineering solutions.
Hands-on expertise in automating and optimizing data workflows with CI/CD and orchestration tools.
Strong problem-solving skills with an analytical mindset and capability to support complex business data requirements.