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Tech Stack
Tools & technologiesAmazon RedshiftBigQueryCloudKafka
About the role
Key responsibilities & impact- 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.
- 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.
- 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.
- 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.
Requirements
What you’ll need- 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.
Benefits
Comp & perks- Flexible paid time off & generous PTO accrual plans
- Comprehensive medical, dental, vision, and other insurances
- FSA & HSA plans for medical and dependent care
- Home office set-up allowance
- Internet stipend
- Retirement plan match for 401k and RRSP
- Gender-neutral paid parental leave, and more!
ATS Keywords
✓ Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
data engineeringdata scienceanalyticsdata architecturemachine learningAI methodologiesdata governancedata qualityMLOpsdata cataloging
Soft Skills
leadershipcommunicationinfluencingcollaborationdata literacystrategic thinkingteam buildinganalytical rigorproblem-solvingcross-functional management
Certifications
advanced degree in Computer Scienceadvanced degree in Statisticsadvanced degree in Mathematics
