We are looking for a Data Analyst for our Risk AI Platform - the group that owns the data and ML infrastructure behind Plata's credit decisioning. At the center of that infrastructure is our feature store: the system that turns raw external and internal data into the features that power our scoring models, both in research and in real-time production. The role sits at the intersection of data engineering, analytics, and ML: you'll spend most of your time in SQL, dbt, Python, and Snowflake, building reliable pipelines and making sure the features our models consume are correct, consistent, and well-monitored - offline and online. Challenges that await you: * Develop and maintain the feature store: design and optimize dbt models across our multi-layer pipeline, from raw ingestion through parsing, unification, and domain modeling to production-ready feature sets. * Onboard new external data sources (credit bureaus, alternative data, identity and scoring providers) into the platform — from raw parsing to production features. * Guarantee consistency between training and serving: build checks and monitoring that catch feature drift, mismatches, and data-quality issues before they reach a model. * Own data quality and observability for the features you ship — freshness, completeness, lineage, and reconciliation. * Work closely with data scientists and ML engineers to productionize features for scoring models, and help turn research feature logic into robust, tested pipeline code. * Improve our tooling, standards, and documentation so the whole team ships features faster and more safely. What makes you a great fit: * 2-3 years of experience in a data engineering, analytics engineering, or strongly engineering-oriented data analyst role. * Strong SQL: you're comfortable writing and optimizing complex queries. * Solid Python for data work (data pipelines, scripting, pandas). * Hands-on experience with dbt, or with building ETL/ELT pipelines you can map onto dbt. * A working understanding of ML — enough to reason about features, training/serving consistency, and how your pipelines feed a model. * A data-quality mindset: you care about correctness, reproducibility, and monitoring, not just getting the number out. * B1 or higher English level for effective communication with an international team Your bonus skills: * Background in Risk, credit, lending, or fintech. * Experience with Snowflake (or a comparable cloud data warehouse) and a cloud platform (AWS). * Familiarity with feature stores, ML model registries. * Comfort with A/B testing and applied statistics. * Experience with orchestration and CI/CD for data. Our ways of working: * Innovative Spirit: A commitment to creativity and groundbreaking solutions * Honest Feedback: valuing open, transparent communication * Supportive Team: a strong, collaborative community * Celebrating Achievements: recognizing our wins together * High-Tech Environment: a team full of smart and revolutionary people who date to challenge the status quo of incumbent finances Our benefits: * Relocation support to one of our hubs — Cyprus, Serbia, Georgia or Kazakhstan — with assistance for the employee and their family * Flexible work from one of our offices or remote * Healthcare Coverage * Education Budget: Language lessons, professional training and certifications * Wellness Budget: Mental health and fitness activity reimbursements * Vacation policy: 20 days of annual leave and paid sick leave