Analytics Engineering Director
US$160,000 – US$180,000 / yr base salary
Posted 19 Aug 2026
Advertised as “Director, Analytics Engineering”
BranchFactor Summary
The original posting with the fluff stripped out
- Expected experience
- 7+ yrs
- Management level
- People management
| Base salary | US$160,000 – US$180,000 / yr |
|---|
Field of studyAnalytics, Applied Mathematics, Business Analytics, Computer Science, Engineering, Statistics
Study levelBachelor's
Study levelMaster's or higher
Overview
Spotter empowers the world's best Creators with capital, data, and insights to scale their programming into sustainable media businesses. Through these partnerships, Spotter helps brands partner with creator-led franchises to unlock growth, amplify impact, and build lasting cultural relevance.
Spotter has already deployed over $1 billion to YouTube Creators to reinvest in themselves and accelerate their growth. With a premium catalog that spans over 725,000 videos, Spotter generates more than 88 billion monthly watch-time minutes, delivering a unique scaled media solution to Advertisers and Ad Agencies that is transparent, efficient, and 100% brand safe. For more information about Spotter, please visit https://spotter.com.
What You’ll Do
As a Director, Analytics Engineering at Spotter, you will lead efforts to deliver cutting-edge analytics engineering solutions that empower data-driven decision-making across the organization. You will play a key role in shaping the analytics engineering strategy, and driving innovation to ensure the organization maintains a competitive edge. In this role, you will collaborate with cross-functional teams, provide technical guidance and mentorship across the team, and establish best practices for Analytics Engineering.
Responsibilities
- Partner with data engineers to ensure smooth, efficient, resilient, and agile knowledge delivery pipelines.
- Interface with other business units to understand analytical needs and deliver datasets/tools in response.
- Identify and capitalize on opportunities to improve ETL (Extract, Transform, Load) processes, increasing scalability, security, extensibility, efficiency, and alignment with organizational goals.
- Collaborate closely with data scientists, business analysts, and senior stakeholders to define analytics requirements and deliver innovative technical solutions that drive business outcomes.
- Collect, organize, structure and profile data to build Analytics Ready Datasets for discovery of meaningful insights.
- Develop, implement, and enforce methodologies for rigorous data quality checks and validation processes to ensure reliability, accuracy, and trustworthiness of data assets.
- Collaborate efforts to identify and resolve data-related challenges and inconsistencies in partnership with data engineering and analytics teams.
- Provide technical guidance and mentorship to analytics engineers, fostering growth, collaboration, and knowledge-sharing across the team.