Director, Analytics Engineering

A+E Networks•New York, NY

5d•$170,940 - $200,000•Hybrid

About The Position

The Director, Analytics Engineering leads a team of analytics engineers and contractors who build trusted analytics capabilities for the Research organization, including its Cross-Platform data foundation. This is a leadership-first, technically credible role. The Director sets direction, develops people, reviews critical designs and code, and selectively steps into complex problems. The role owns hiring, performance management, and engineering standards; works with the SVP on roadmap prioritization; and partners with IT Engineering on deployment, monitoring, and production operations. The Director translates ambiguous stakeholder needs into scoped solutions, prioritizes work based on value, capacity, and risk, and communicates progress and outcomes to technical and nontechnical audiences. The role also guides forecasting, propensity, segmentation, and attribution work; builds these capabilities within the team; and evaluates emerging analytics, AI, and agent-based capabilities for responsible adoption.

Requirements

10+ years of progressive experience in analytics engineering, analytics, or data engineering, including 5+ years leading technical teams.
Demonstrated success hiring, coaching, and managing the performance of analytics or data professionals.
Bachelor’s degree in a quantitative or technical field, or equivalent practical experience.
Advanced SQL and strong Python skills.
Experience governing transformation workflows in Snowflake with Git-based development practices.
Working fluency in applied statistics and predictive modeling sufficient to scope, review, and direct data science work.

Nice To Haves

Pragmatic player-coach with strong judgment who earns trust with skeptical or self-sufficient stakeholders through delivery rather than positional authority, and operates well through ambiguity and change.
Experience in media and entertainment or another data-rich, fast-changing industry.

Responsibilities

Hire, coach, and develop analytics engineers; own performance management, career growth, and capability planning.
Set and enforce standards for data modeling, trusted metrics, testing, and governance.
Keep engineers focused and productive when requirements change mid-project.
Manage contractors and distributed delivery partners as an extension of the team.
Translate ambiguous needs from senior stakeholders into scoped, deliverable solutions.
Prioritize work based on value, capacity, and risk, and hold scope steady as requirements evolve.
Build trust through delivery and follow-through, and communicate progress, risks, and outcomes to technical and nontechnical audiences.
Set readiness standards and handoffs with IT Engineering so solutions move into production operations and the team can step off support.
Guide forecasting, propensity, segmentation, and attribution work, and build those capabilities within the team.
Evaluate emerging analytics, AI, and agent-based capabilities and guide responsible adoption.
Review critical designs and code and selectively step into complex problems.
Work with the SVP on roadmap prioritization and partner with IT Engineering on deployment, monitoring, and production operations.