Set and own the company-wide data strategy across engineering, analytics, acquisition, and operations
Build and lead a multi-disciplinary data organization with clear charters, ownership, and accountability
Translate company and product priorities into a coherent data roadmap
Establish success metrics for data reliability, coverage, quality, and business impact
Own the design and evolution of Wizard’s data architecture covering ingestion, compilation, auditing, and analytics
Ensure systems scale reliably as data volume, product complexity, and customer usage grow
Balance near-term execution with long-term architectural health and flexibility
Oversee large-scale data acquisition through web crawling, third party APIs, and data feeds in various formats as a core product input
Ensure Spark-based data compilation pipelines are efficient, resilient, compliant, and adaptable to changing sources
Partner closely with AI/ML and product teams to align data acquisition with model and product needs
Lead the analytics function that supports product, growth, operations, and leadership decision-making
Ensure data is accessible, trusted, and well-modeled for both technical and non-technical stakeholders
Drive standards for metrics definition, reporting, and experimentation
Own data quality, observability, incident response, and operational rigor across all data systems
Establish governance, privacy, and security practices appropriate for scale and regulatory expectations
Ensure strong documentation, operational readiness, and clear escalation paths
Serve as a senior thought partner to Product, AI/ML, Engineering, and Leadership
Influence roadmap decisions by grounding discussions in data realities and tradeoffs
Act as the primary executive owner for data across the organization

Requirements

12+ years of experience across data engineering, data platforms, or analytics, with significant leadership scope
6+ years leading senior managers and/or directors in complex data organizations
Proven experience owning end-to-end data systems in a production, cloud-based environment (AWS, GCP, or Azure)
Deep understanding of large-scale data ingestion, pipelines, analytics, and operational reliability using Apache Spark for parallel processing and Airflow for orchestration
Strong judgment in balancing speed, quality, cost, and long-term maintainability
Ability to operate comfortably at both strategic and deeply technical levels
Bachelor’s or Master’s degree in Computer Science, Data Science, or a related field, or equivalent experience

Benefits

Equity in the form of stock options
Medical, dental, and vision coverage
401(k) plan
Flexible PTO and company holidays
Fully remote work within the United States
Periodic company-wide offsites and team gatherings

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard skills

data strategydata architecturedata ingestiondata pipelinesdata analyticsdata qualitydata governancedata modelingApache SparkAirflow

Soft skills

leadershipstrategic thinkingjudgmentcommunicationcollaborationinfluencingaccountabilityoperational rigordocumentationproblem-solving