1 день назад
Data Engineering Lead - Senior Vice President (AI)
200 000 - 250 000$
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Data Engineering Lead - Senior Vice President (AI) (Snowflake/Databricks): Leading the evolution of an enterprise data platform that powers AI, automation, analytics, and data-driven decision making with an accent on cloud architecture, semantic layers, governance, and scalable data products. Focus on defining multi-year platform strategy, building high-performing engineering organizations, and designing secure, observable, AI- and ML-enabled data capabilities for regulated financial services.
Location: New York, New York, United States; office attendance required Monday–Thursday, with remote work available on Friday
Base salary: $200,000–$250,000 per year, plus equity and an annual performance bonus.
Company
provides technology and investment solutions for financial services, including wealth management and alternative investments.
What you will do
- Define and own the enterprise data architecture, including Snowflake, semantic layers, reusable data products, and an AI-ready ecosystem.
- Establish standards for data engineering, governance, security, observability, quality, documentation, and DataOps.
- Own platform reliability, service levels, incident management, tooling decisions, and investment recommendations.
- Develop and execute a multi-year Data Engineering roadmap aligned with business and AI priorities.
- Partner with business and technology leaders to deliver scalable data products and communicate progress, risks, and investment decisions to executives.
- Build and lead a high-performing Data Engineering organization through hiring, organizational design, and leadership development.
Requirements
- 12+ years of data engineering experience, including 5+ years leading large-scale engineering organizations across multiple functions.
- Experience designing, building, and operating enterprise cloud data platforms such as Snowflake or Databricks, including architecture, security, governance, and cost optimization.
- Expertise in pipeline design, data quality, observability, data contracts, documentation, operational support, and semantic layer development.
- Experience developing multi-year platform strategies, securing investment, prioritizing initiatives, and presenting technical concepts to executive stakeholders.
- Financial services experience in asset management, wealth management, fintech, banking, or insurance, with knowledge of regulated data environments.
- Experience with Snowflake, dbt, AI- and ML-enabled data platforms, and enterprise data catalog, metadata management, or MDM platforms such as Informatica.
Culture & Benefits
- Hybrid work model with office attendance Monday–Thursday and remote work on Friday.
- Equity for all full-time employees and an annual performance bonus.
- Employer-matched retirement plan and subsidized healthcare.
- Employer-paid dental, vision, telemedicine, and virtual mental health counseling.
- Parental leave and unlimited paid time off.
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