VP - Senior Data Engineer (Python/Snowflake/Apache Airflow)
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Protocol Intelligence
Data-driven signals on your job's competitivenessTier-1 brand, metro location, generalist data engineer title, and broad skill requirements produce high applicant competition.
Medium—core data engineering skills are transferable but enterprise finance context increases domain specificity.
High—explicit 8+ years and mandatory Snowflake, Airflow, dbt, Python experience for a VP data engineering role.
Job Description
Structured overview of role & requirementsAbout This Role
Design, develop, and optimize enterprise-scale data platform capabilities using Python, Apache Airflow, Snowflake, dbt, and cloud-native technologies.
Build and manage large-scale data pipelines, metadata-driven processing frameworks, and enhance platform features like data quality, governance, and workflow orchestration.
Lead technology evaluations, support production operations through L2/L3 support, mentor junior engineers, and drive continuous improvements in platform performance and reliability.
Minimum Requirements
Bachelor’s degree in Computer Science, Information Systems, or related field.
8+ years of experience in Data Engineering or Data Platform Engineering role.
Hands-on expertise with Apache Airflow, Python, Snowflake (or equivalent cloud-native analytical data platform), dbt, and complex SQL optimization.
Experience with cloud platforms (Azure, AWS, or GCP), streaming technologies (e.g., Kafka, Snowpipe), and containerized environments (Docker, Kubernetes).
Ideal Candidate Profile
Experienced leader capable of driving technical design decisions, mentoring engineers, and collaborating with cross-functional teams in enterprise-scale data environments.
Proficient in emerging technologies such as Agentic AI and AI-native tools to enhance data platform automation and developer productivity.
Skilled in scalable, performance-driven system design, continuous delivery pipelines, and operational governance in modern cloud-native data platforms.