Vp, Data Architecture & Solutions

Dentsu Creative ANZ

New York, New York, US
Base: $136,000 - $200,000; bonus/equity: discretio...
Fully remote
Azure/databricks/python/pyspark stack
Agentic data systems
Third-party analytics partners
Help build the foundational data infrastructure that powers everything Dentsu’s Decisioning practice delivers

Job Summary

  • Help build the foundational data infrastructure that powers everything Dentsu’s Decisioning practice delivers.
  • Own the enterprise data architecture strategy across Azure, Databricks, ADLS, PySpark, and Power BI—defining reference patterns used across client engagements.
  • Benefits available with this position include: Medical, vision, and dental insurance, Life insurance, Short-term and long-term disability insurance, 401k, Flexible paid time off, At least 15 paid holidays per year, Paid sick and safe leave, and Paid parental leave.

Matching Summary

Help build the foundational data infrastructure that powers everything Dentsu’s Decisioning practice delivers.

Salary

Base: $136,000 - $200,000; Bonus/Equity: discretionary incentive compensation; Benefits: Medical, vision, and dental insurance, Life insurance, Short-term and long-term disability insurance, 401k, Flexible paid time off, At least 15 paid holidays per year, Paid sick and safe leave, and Paid parental leave.

Skills & Requirements

Must-have

  • Azure/Databricks/Python/PySpark stack
  • Agentic data systems
  • Third-party analytics partners
  • AI orchestration tools
  • Enterprise data architecture strategy
  • Data foundation for Genie spaces
  • Data governance and security standards

Nice-to-have

  • Media agency experience
  • Advertising technology environments
  • Managing offshore engineering teams
  • Media data sources knowledge

Key Requirements

  • 10+ years of experience in data engineering and architecture
  • Deep expertise in Databricks, Apache Spark, and modern lakehouse architecture
  • Strong experience with the Azure ecosystem
  • Demonstrated experience building and leading data engineering teams
  • Expert knowledge of PySpark, data modeling, and enterprise-scale transformation frameworks
  • Experience designing multi-tenant data platforms
  • Strong understanding of data governance, data quality frameworks, and taxonomy management

Work Rights

Not specified

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