Chief Data Officer Jobs in San Ramon, CA (NOW HIRING)

• Define and execute the strategy for Trustly's global data platform, including data lakehouse architecture, streaming and batch pipelines, data cataloging, observability, and correctness.
• Own the end-to-end data engineering function, ensuring reliable, scalable, and cost-efficient data infrastructure that serves product, analytics, risk, and compliance use cases across all geographies.
• Drive the evolution of Trustly's data stack, making deliberate build-vs.-buy decisions and managing a best-in-class ecosystem of data tools and vendors.
• Establish and enforce data standards, taxonomy, and governance frameworks that enable self-service access without sacrificing data quality or integrity.
• Partner with Engineering and Infrastructure teams to ensure the data platform meets the availability, security, and regulatory requirements of a globally operating payments company.

Data Strategy & Key Datasets

• Identify, develop, and steward Trustly's highest-value proprietary datasets, including transaction-level payment data, bank account intelligence, consumer behavioral signals, and merchant performance data.
• Define a long-term data strategy that turns Trustly's unique data assets into durable competitive advantages - for risk management, product differentiation, and potential new revenue streams.
• Oversee data governance, data lineage, and master data management programs, ensuring a single source of truth across the organization.
• Champion data quality and reliability as foundational standards, implementing frameworks that ensure confidence in data used for business-critical decisions.
• Collaborate with Legal, Compliance, and Privacy teams to ensure responsible and lawful use of data across all jurisdictions, including under GDPR, CCPA, and relevant open banking data regulations.

• Build and lead a world-class analytics function that delivers actionable insight to business stakeholders across Product, Finance, Risk, Operations, Sales, and the C-suite.
• Establish a self-service analytics culture, enabling non-technical teams to access, explore, and act on data confidently and safely.
• Own the development of key performance metrics, executive dashboards, and board-level reporting, ensuring data is accessible, accurate, and impactful at every level of the organization.
• Partner with merchant-facing teams to develop external analytics products and insights that deepen Trustly's value proposition with key partners and enterprise clients.

Machine Learning & Artificial Intelligence

• Lead Trustly's machine learning and AI program, setting the technical vision and organizational structure for applied ML across fraud detection, risk scoring, payment success optimization, personalization, and operational automation.
• Build and grow a team of machine learning engineers and data scientists, establishing rigorous practices for model development, validation, deployment, and monitoring.
• Drive the responsible adoption of generative AI and large language models where they can create meaningful productivity or product value, with appropriate governance and oversight.
• Define and maintain Trustly's AI ethics and model risk management framework, ensuring fairness, explainability, and regulatory compliance across all deployed models.
• Stay current with the rapidly evolving AI/ML landscape and translate emerging capabilities into concrete business opportunities for Trustly.

Leadership & Cross-Functional Partnership

• Recruit, develop, and lead a high-performing, global team of data engineers, analytics engineers, data scientists, ML engineers, and BI analysts.
• Foster a data-driven culture across Trustly, partnering with senior leaders to raise the overall level of data literacy and analytical rigor in decision-making.
• Represent Trustly's data capabilities externally with partners, regulators, and the broader industry, where relevant.
• Contribute to the broader technology leadership team, collaborating with the CTO and peer executives on cross-cutting strategy and resource allocation.

• 15+ years of progressive experience in data engineering, data science, analytics, or a closely related technical discipline, with at least 5 years in a senior leadership role.
• Demonstrated success building and scaling data platforms and teams in high-growth, data-intensive technology or financial services environments.
• Deep expertise in modern data architecture: cloud data warehouses (Snowflake, BigQuery, Redshift), data lakes, streaming platforms (Kafka, Flink), and orchestration frameworks.
• Hands-on understanding of machine learning and AI methodologies, with experience overseeing applied ML programs in production at scale.
• Strong command of data governance, data quality, and regulatory compliance requirements relevant to financial services and global data privacy law (GDPR, CCPA).
• Track record of translating complex data strategy into business outcomes, with the communication skills to influence C-suite and Board-level audiences.
• Experience managing geographically distributed, cross-functional data teams in a global organization.
• Prior CDO, VP of Data, or equivalent executive title at a technology company, payments platform, or regulated fintech.
• Experience in payments, open banking, financial services, or another highly regulated, data-rich industry.
• Familiarity with transaction-level payment data, fraud modeling, credit risk scoring, or consumer behavioral analytics in a financial context.
• Proven experience building or scaling ML platforms and MLOps infrastructure for production model deployment and monitoring.
• Experience with generative AI and large language model deployment in an enterprise context.
• Advanced degree (M.S. or Ph.D.) in Computer Science, Statistics, Mathematics, or a related quantitative field, or equivalent practical experience.