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Niche Snowflake specialist and senior level reduces competition despite metro location.
Medium because Snowflake and data engineering skills transfer, but financial preference and deep Snowflake expertise increase specificity.
High due to explicit 10+ years, mandatory 6+ years Snowflake experience, and certification requirement.
Design, build, and optimize scalable Snowflake data solutions including databases, schemas, warehouses, and workload management.
Build and manage end-to-end data pipelines with tools like dbt, Python, Airflow/ADF, ensuring performance tuning, data governance, and secure access.
Take full ownership of design, development, deployment, and support of Snowflake data engineering initiatives with minimal oversight, collaborating with architects and stakeholders.
10–12 years of hands-on data engineering experience with at least 6 years dedicated to Snowflake.
Bachelor's degree in Engineering (B.E./B.Tech), MCA, MBA in Information Systems, Computer Science or related field.
Snowflake Certification (e.g., SnowPro Core or Advanced Data Engineer) required.
Experience with SQL, Python, cloud data ecosystem (Azure/AWS), dbt, Airflow/ADF, REST/SOAP API integration, and enterprise platform connectivity.
Deep technical expertise in Snowflake architecture, Medallion data modeling, and cloud-native integrations ensuring scalable and cost-efficient solutions.
Proven ability to independently own complex Snowflake data engineering projects end-to-end in enterprise environments, preferably with financial domain exposure.
Experienced in DevOps practices including CI/CD workflows, code reviews, and automated deployment within Snowflake and cloud ecosystems.