Vice President, Analytics Engineering

Key Skills

Apache Airflow, Apache Kafka, Big Data Technology, Business Intelligence, Data Lake, Data management, Data Modeling, Data science techniques, Data Warehousing, Design, ETL frameworks, Google BigQuery, PowerBI, Python Programming, SPARK Programming, SQL, Tableau

Job Description

Overview: 

Spotter, named one of TIME100's Most Influential Companies this year, empowers top YouTube creators to accelerate their business and unleash their full creative potential by giving them access to the capital, knowledge, and community they need to succeed at scale. As the top provider of creator-friendly growth capital, Spotter tailors our investments to meet the unique needs of each creator we partner with, giving them the freedom to create without compromise.

Creators are free to reinvest their funds however they choose, from hiring a team, to building their own production studios, and everything in between, all while maintaining total control over their catalogs, their channels, and their future earnings. In addition to funding, Spotter provides creators with in-depth data insights into the performance of their existing content, enabling them to leverage the full value of their library, as well as the value of future uploads and how they can improve performance in the future.

Featured in Forbes, Fast Company, Variety, Axios, and more, Spotter has already deployed over $740 million to YouTube creators to reinvest in themselves and accelerate their growth. Spotter has licensed content that consists of over 600,000 videos, which generate 88 billion monthly watch-time minutes. With our curated premium video catalog, we deliver a unique scaled media solution to Advertisers and Ad Agencies that is transparent, efficient, and 100% brand safe.

What You’ll Do

The VP, Analytics Engineering role plays a critical role in both strategic and tactical operations that support all analytics and data science activities at Spotter. This role will be tightly integrated with the highest levels of the leadership team in daily operational execution and long-term strategic knowledge development.

Responsibilities

• Play role of trustee of critical knowledge that transforms raw data into information
• Design, build, and deploy analytics ready datasets by processing petabytes of data on a regular basis
• Deliver near-real-time and non-near-real-time data and applications to a team of analysts and data scientists who create insights and analytics applications for our stakeholders
• Participate in data strategy and road map exercises, business intelligence/data warehouse product selection, design, and implementation
• Lead in exploring new data sources that are important in maintaining and advancing the company’s competitive advantage
• Interact with engineering on our in-house highly available data collection and real time data processing pipeline for the analytics team's needs
• Lead ETL Design and Development, contribute to the development of a big data platform using modern pipeline technologies such as Spark, Kafka, Airflow
• Curate the “business-ready” data catalog for analysts and researchers 
• Own the visualization tools and development of all reports and dashboards
• Support and train business users on how to use data to present information correctly in visualization tools
• Own the design, development, and maintenance of ongoing metrics, reports, analyses, dashboards, etc to drive key business decisions

Who You Are

• BS/MS in Computer Science, Engineering, Mathematics or other quantitative discipline
• Expert in normalization/denormalization techniques for data analysis and optimum performance in a big data environment 
• Must have hands-on experience in modern data pipeline applications
• Strong work experience in in data warehouse, data lake design, data modeling and data management
• Experience developing and managing data warehouses on a terabyte or petabyte scale
• Strong experience in massively parallel processing & columnar databases
• Expert in either: Redshift / Big Query / Snowflake or similar stack
• 7+ years of work experience with ETL, data modeling, and business intelligence big data architectures
• Expert in at least SQL or Python, preferably both
• Advanced skills in data visualization tools like Power BI, Tableau or similar tools

Nice to have experience:

• Knowledge of YouTube or Content Creator industry
• Streaming data systems such as Kafka and Spark Streaming
• Distributed processing using tools such as Spark, Hevo etc
• Scheduling and orchestration tools such as Airflow

Why Spotter

• Medical & vision insurance covered up to 100%
• Dental insurance
• 401(k) matching
• Stock options
• Complimentary gym access
• Autonomy and upward mobility
• Diverse, equitable, and inclusive culture, where your voice matters.

In compliance with local law, we are disclosing the compensation, or a range thereof, for roles that will be performed in Culver City. Actual salaries will vary and may be above or below the range based on various factors including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The overall market range for roles in this area of Spotter are typically: $100-$800K salary per year. The range listed is just one component of Spotter’s total compensation package for employees. Other rewards may include annual discretionary bonus and equity.