Data Engineering Lead - Senior Vice President

What you'll do

• Define and oversee enterprise data architecture, engineering standards, governance, security, reliability, and DataOps.
• Set and deliver the multi-year data engineering roadmap, platform strategy, and investment priorities in alignment with business and AI goals.
• Build and lead the Data Engineering organization and partner with business, technology, and executive stakeholders.

What they ask for

• 12+ years of data engineering experience, including 5+ years leading large-scale engineering organizations across multiple functions.
• Proven experience designing, building, and operating enterprise-scale cloud data platforms, including architecture, security, governance, and cost optimization.
• Deep expertise in data engineering practices and Snowflake architecture, performance optimization, security, and data sharing at enterprise scale.
• Experience presenting to executive stakeholders in regulated industries and delivering multi-year platform strategies with measurable business outcomes.

Nice to have

• Financial services experience, including knowledge of regulated data environments and governance requirements.
• Experience with analytics engineering and semantic layers, AI/ML-enabled data platforms, dbt, or Informatica or comparable platforms.

Pay

USD $200,000 to $250,000 base salary

Tools

Snowflake, Databricks, dbt, Informatica

AI focus

Lead development of an AI-ready data ecosystem and future AI enablement initiatives; experience with AI- and ML-enabled platforms, semantic layers, feature stores, model-serving infrastructure, or LLM-integrated architectures is sought.