Responsibilities
- Define and manage a long-term data platform roadmap that aligns infrastructure, tooling, and staffing with strategic business goals.
- Manage and develop two high-performing teams in Data Engineering and Analytics Engineering, fostering collaboration, feedback, and clear career progression.
- Design and oversee scalable data pipelines for both batch and real-time processing across ingestion, transformation, orchestration, and delivery layers.
- Promote strong analytics engineering practices, including semantic modeling, standardized dbt frameworks, data contracts, and metrics governance.
- Collaborate with Data & Decision Science, Product, Finance, and Commercial teams to deliver reliable, self-service data solutions that meet business needs.
- Ensure the data platform operates reliably with defined SLAs, monitoring, observability, and incident response protocols, treating it as a product serving internal users.
- Lead evaluations of third-party tools and vendors across the modern data stack, including cloud data warehouses, orchestration, cataloging, transformation, and reverse ETL platforms.
- Establish and enforce standards for data quality, documentation, and governance to ensure trust and consistency across the organization.
- Advocate for AI-assisted development by integrating coding assistants and LLM-powered tools like Cursor, GitHub Copilot, and Claude to improve productivity and reduce manual effort.
- Design intelligent data pipelines using AI-native techniques such as LLM-generated documentation, anomaly detection, automated data quality checks, and root-cause analysis.
- Develop prototypes for natural language interfaces that convert NL queries to SQL and enable AI-driven business intelligence tools for non-technical users.
- Build foundational infrastructure to support AI and machine learning initiatives, including feature stores, vector databases, model metadata systems, and evaluation datasets.
Benefits
- Competitive pay and inclusion in the company ownership program to align employee success with company performance.
- Flexible work model with remote, hybrid, and in-office options based on role, team, and location.
- Generous paid time off, including local holidays and a company-wide break in late December to encourage rest and recovery.
- Comprehensive wellness and mental health support programs.
- Access to learning and development resources, including professional growth tools and tuition reimbursement.
- Provision of necessary technology and equipment to enable high-performance work.
- Employee recognition through the Motivosity platform.
- Inclusive culture emphasizing support, belonging, and meaningful team connections.
Compensation
Competitive compensation with participation in the ownership program for all full-time employees
Work Arrangement
Remote (Worldwide)
Team
Lead and grow two high-performing teams—Data Engineering and Analytics Engineering
Other
- All hires must successfully complete a background check as part of the onboarding process.
- Candidates may be required to confirm their legal name, current physical location, valid contact number, and residential address, in compliance with local data privacy regulations.
- Any misrepresentation of personal or professional details will lead to immediate disqualification from the hiring process.
