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Tier-1 brand and metro location increase competition, but Snowflake/Airflow specificity reduces applicant density.
Core data engineering skills transfer across industries, though healthcare domain exposure increases preference moderately.
Multiple mandatory technologies and architecture ownership increase filtering, but no explicit years stated.
Design and implement scalable enterprise data warehouse and data engineering solutions using Azure, Snowflake, Python, and Apache Airflow.
Architect and develop robust ETL/ELT pipelines for structured and unstructured data from multiple enterprise and external systems.
Lead technical solution design discussions, establish best practices, mentor development teams, and drive delivery execution across multiple initiatives.
Bachelor’s degree in Computer Science, Engineering, Information Systems, or related technical field required; advanced degree preferred.
Strong hands-on experience with Microsoft Azure cloud platform, Python development, Snowflake data warehouse, and Apache Airflow.
Experience supporting enterprise-scale production platforms with high availability requirements.
Work Experience Required: Not explicitly mentioned in the JD.
Experienced in enterprise data engineering with a focus on cloud-native, scalable, and high-availability solutions.
Capable of leading technical discussions and mentoring teams on best practices and performance optimization.
Familiar with Agile/Scrum methodologies and enterprise integration/API-based architectures.