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Metro location and common data tooling yield moderate applicant density despite senior level.
Data engineering skills (Snowflake, dbt, ETL) are broadly transferable across industries.
Explicit 8+ years and mandatory Snowflake/dbt/Fivetran/Python/SQL increase filtering.
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Lead design and development of scalable ETL data pipelines focusing on integration, transformation, and loading.
Architect and maintain cloud-based data warehouses, lakes, and marts primarily on Snowflake.
Mentor junior data engineers and collaborate with stakeholders to align data solutions with business goals.
Bachelor's or master's degree in Computer Science, Data Science, or related field.
Minimum 8 years of data engineering experience.
Strong expertise with Snowflake and proficiency in ETL tools, especially Fivetran, and data orchestration using dbt.
Programming skills in Python or Java, with experience in SQL, database design, version control (Git/DevOps), and Agile methodologies.
Experienced in building and maintaining cloud-based scalable data platforms, particularly with Snowflake.
Capable of mentoring junior engineers and leading design decisions related to data engineering architecture.
Comfortable working closely with cross-functional teams including data scientists, analysts, and business stakeholders to drive strategic data initiatives.
