Vice President, Analytics Engineering

Spotter is seeking a VP of Analytics Engineering to play a critical role in supporting all analytics and data science activities. This role involves designing and building analytics-ready datasets, delivering data and applications to analysts and data scientists, and participating in data strategy and roadmap exercises. The VP will also explore new data sources, interact with engineering on data collection and processing pipelines, curate a business-ready data catalog, and own the development of reports and dashboards. This position is based in Los Angeles.

• 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

• 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 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 Conte

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