Staff Data Product Manager — GTM Analytics (Remote)

Twilio; United States; On-site; USD 164,000 - 228,700; Full time

Benefits offered by this job

Equity plan

Corporate bonus plan

Health care insurance

401(k) retirement account

Paid sick time

Paid personal time off

Paid parental leave

Job summary

Twilio is seeking a Staff, Data Product Manager for GTM Data Science & Analytics to lead the strategy, roadmap, and lifecycle of data products across the organization. You will turn raw data into structured, usable assets that drive decision-making, automation, and personalization.

You will bridge data engineering, data science, and business teams to deliver scalable data solutions, ensure data accessibility and trust, and define metrics that demonstrate impact.

Qualifications

• 8 years of experience in product management, engineering, or analytics with a focus on data products, analytics platforms, or data infrastructure, with a preference for direct experience supporting GTM or sales analytics in a SaaS environment.
• Strong understanding of data platforms, data pipelines, and analytics/BI tools (e.g., AWS, Snowflake, DBT, Tableau).
• Proficiency with SQL and familiarity with data modeling concepts.
• Experience working with data teams (engineering, analytics, and data science).
• Knowledge of data governance, privacy regulations, and data security standards.
• Strong communication and collaboration skills, with the ability to work across technical and non-technical stakeholders.
• Experience with agile product development methodologies.
• Strong project management skills, with the ability to prioritize and execute multiple initiatives simultaneously.
• Strong analytical and problem-solving skills with the ability to translate data insights into actionable strategies.

Responsibilities

• Define and own the vision, strategy, and roadmap for data products (e.g., dashboards, data platforms, model features and enhancements) that support data-driven insights, decisioning, and actions.
• Act as the bridge between data engineers, data scientists, analysts, and business stakeholders to translate business needs into data solutions.
• Develop product requirements and user stories focused on data access, usability, performance, and quality.
• Prioritize data initiatives based on business impact, technical feasibility, and data availability.
• Ensure proper data governance, privacy, and compliance practices are followed.
• Ensure teams have self-service access to GTM data via platforms, tools, and interfaces.
• Monitor and improve data quality, reliability, and user adoption of data tools and features, providing regular reporting on effectiveness and areas for improvement.
• Define and track success metrics for data products, ensuring they meet business and technical goals.
• Foster a culture of data-driven decision making by making data products intuitive and accessible.
• Partner with finance, product, and sales teams to ensure that data products serve the needs of our internal customers.
• Stay informed about industry trends, tools, and best practices in data product management and data enablement.
• Develop training materials to empower teams across the organization to use data effectively for decision-making, campaign execution, and customer engagement.
• Lead initiatives to improve data literacy across teams, ensuring that data is accessible, understandable, and actionable.
• Identify opportunities for innovation in how we leverage data, driving new methodologies and technologies to enhance data utilization and customer experience.

Skills

Data platforms

Data pipelines

Analytics/BI tools

SQL

Agile

Project management

Communication

Data governance

Education

Advanced degree (MBA, Master’s in Engineering, Analytics, Data Management or related fields)

Tools

AWS

Snowflake

DBT

Tableau

Job description

Twilio is seeking a Staff, Data Product Manager for GTM Data Science & Analytics to lead the strategy, roadmap, and lifecycle of data products across the organization. You will turn raw data into structured, usable assets that drive decision-making, automation, and personalization.

You will bridge data engineering, data science, and business teams to deliver scalable data solutions, ensure data accessibility and trust, and define metrics that demonstrate impact.