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Tier-1 brand and metro location increase competition, but senior leadership and specialized skillset limit applicant density.
Core data engineering leadership is transferable, but Marketing Tech and Snowflake expertise increase domain-specificity.
Explicit 12+ years, 6+ management years, and specific Snowflake/dbt/airflow requirements make filters strict.
Lead and manage a team of 3+ senior data engineers focused on marketing technology data platforms.
Architect, build, and optimize scalable data pipelines, data models, and ETL/ELT workflows across data warehouses and lakehouses.
Serve as primary data engineering representative in cross-functional planning, stakeholder communication, and support intake management, ensuring SLAs are met.
12+ years of data engineering experience including cloud data warehouse/lakehouse architecture.
6+ years of people management experience, managing senior or staff-level engineers.
Proficiency in SQL and Python; experience with Snowflake, lakehouse table formats (Iceberg or similar), and pipeline orchestration tools (Airflow, dbt, or similar).
Work Experience Required: 12+ years in data engineering; 6+ years in people management.
Experienced in managing and scaling senior engineering teams within data engineering focused on marketing technology or analytics platforms.
Strong technical leadership with hands-on expertise in cloud data platforms, ETL/ELT pipeline architecture, dimensional modeling, and data governance.
Proven ability to collaborate effectively with marketing, analytics, and engineering leadership to translate business requirements into technical solutions.