4 months ago
Brussels, Belgium or London, United KingdomStaff+
Responsibilities
- Define data platform architecture and deliver projects and initiatives end-to-end.
- Act as a technical reference point by setting standards for quality, testing, observability, data modeling, and documentation.
- Design and build scalable, performant, reliable real-time and batch data pipelines for high-volume payment transactions.
- Establish standards for AI-assisted development, automated data quality testing, and LLM-powered data workflows.
- Design data models supporting fraud detection, revenue analytics, payment success optimization, and regulatory reporting.
- Own platform reliability, including SLAs, data quality, alerting, and incident response for data services.
- Ensure secure data handling aligned with PCI-DSS, GDPR, and other relevant compliance frameworks.
- Partner with Product, AI, and Finance teams to translate business needs into scalable data solutions.
- Contribute to the data platform roadmap and identify opportunities to create business value through data.
- Mentor senior and mid-level engineers through code reviews, design reviews, and knowledge-sharing sessions.
- Collaborate with analysts, data scientists, and product managers to deliver reliable, documented, fit-for-purpose data products.
Requirements
- 8+ years of experience in data engineering, software engineering, or a related field, including at least 2 years at staff or principal level.
- Deep expertise designing and building large-scale data platforms using streaming, batch, or hybrid architectures.
- Hands-on experience with Spark, Flink, Kafka, StarRocks, or equivalent technologies.
- Strong Python and SQL skills, with comfort across multiple languages and paradigms.
- Understanding of dimensional modeling, Data Vault, or lakehouse patterns.
- Experience with cloud data infrastructure on AWS, GCP, or Azure, including managed storage, compute, and orchestration services.
- Strong understanding of data quality, observability, and governance principles.
- Ability to set standards and lead technical initiatives across multiple teams without direct authority.
- Professional proficiency in written and spoken English.
- Payments or fintech industry experience is preferred.
- Familiarity with dbt, Great Expectations, or similar tools is preferred.
- Experience with event-driven services and data mesh approaches is preferred.
- Exposure to ML platform design or feature store infrastructure is preferred.
Benefits
- Remote work from anywhere.
- One-time home office bonus.
- Work equipment.
- Stock options.
- Health plan wherever the employee is located.
- Flexible days off.
- Language, professional, and personal growth courses.
Tech Stack
Categories
Data Engineering
