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Metro location, mid-level role, popular data engineer title, and strong employer brand increase candidate competition.
Data engineering skills are transferable across industries but Snowflake/DBT expertise creates moderate domain specificity.
Explicit 5+ years requirement plus mandatory Snowflake, DBT, Airflow, Python and leadership skills raises strictness.
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Design, build, and optimize scalable data models and ELT pipelines using Snowflake and DBT.
Lead and manage technical teams, conduct code reviews, and mentor team members on Snowflake-based solutions.
Develop and automate data workflows using Python scripting and orchestrate with DBT and Airflow, ensuring performance and reliability.
Bachelor’s degree in Computer Science, Information Technology, or related field.
Minimum 3 years of experience as a Data Engineer or similar role with Snowflake expertise.
Proficiency in Snowflake, Python scripting, SQL, DBT (Data Build Tool), and Airflow for data orchestration.
Experience designing and optimizing ETL/ELT data pipelines and scalable data solutions.
Experienced in leading and mentoring technical teams in Snowflake data solution projects.
Strong technical expertise in building, optimizing, and automating data workflows with Snowflake, DBT, Python, and Airflow.
Capable of collaborating effectively with cross-functional stakeholders to translate data requirements into technical deliverables.