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Tier-1 brand, metro location, mid-level in-demand Snowflake/data skills create high candidate competition.
Snowflake and cloud data engineering skills are transferable across industries but require tooling expertise.
Mandatory SnowPro certification, explicit 5–8 years, and specific Snowflake/AWS/DBT skills make screening strict.
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Design, develop, optimize Snowflake data pipelines and data models, ensuring performance and cost efficiency.
Implement and maintain DBT workflows and orchestrate data workflows using Apache Airflow or similar tools.
Collaborate with stakeholders to understand data requirements and leverage AWS cloud services (Glue, Lambda, Step Functions) for scalable data solutions.
5–8 years of relevant experience in data engineering or related roles.
Mandatory skills: Snowflake (SnowPro Core certification required), SQL, Data Modelling, Python, AWS Glue, Lambda, Step Functions.
Experience with DBT workflows, Apache Airflow (or similar), and CI/CD tools (Git, Jenkins, Azure DevOps).
Educational qualification: Bachelor or Master of Engineering, or MBA.
Experienced in modern cloud data platforms, specifically Snowflake and AWS ecosystem, with solid hands-on in data pipeline automation and orchestration.
Aptitude for building scalable, optimized data solutions using SQL, Python scripting, and data modeling in collaborative environments.
Certified SnowPro Core and familiar with delivering end-to-end data engineering workflows, including performance tuning and cost optimization.