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Tier-1 brand, mid-level data engineer, popular title and metro location increase competition.
Modern data engineering stack (Airflow, Snowflake, dbt, Python) is highly transferable across industries.
Explicit 5+ years and mandatory Snowflake, Airflow, dbt, Python and Azure skills enforce high filtering.
Design, develop, test, deploy, and maintain Enterprise Data Platform core framework components including data pipelines and orchestration.
Collaborate with product managers, data owners, platform teams through full SDLC, contributing to project planning, design decisions, and adoption of new tools.
Provide L2/L3 support and conduct end-to-end testing to ensure production reliability and scalability of data engineering solutions.
Minimum 5+ years of experience as a data engineer.
Proficiency in SQL (including stored procedures and UDFs), advanced Python programming, and experience with Snowflake or similar cloud-native databases.
Experience with data orchestration tools (especially Airflow), dbt for data transformation, and Azure services especially ADLS or equivalent.
Bachelor's degree in computer science is strongly preferred.
Experienced with Agile development methodologies including SDLC ownership and working in matrixed organizations.
Strong technical expertise operating modern data engineering tools for building performant, scalable data frameworks and pipelines.
Ability to coordinate cross-functionally with diverse stakeholders and provide higher-level technical support and documentation.