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Data Analyst Middle/Middle+ [Risk] at Plata Card. . Location: Worldwide. . . . . . . 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. . . . . . . . .