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.

• 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

• 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