Data Analyst (Fintech)

TL;DR

Data Analyst (Fintech): Developing and maintaining the feature store and ML infrastructure for credit decisioning with an accent on dbt modeling, data quality, and pipeline reliability. Focus on productionizing research features, onboarding external data sources, and ensuring training-serving consistency.

Location: Worldwide (Remote). Relocation support available to Cyprus, Serbia, Georgia, or Kazakhstan.

Company

hirify.global develops a Risk AI Platform for automated credit decisioning and scoring.

What you will do

• Design and optimize dbt models across a multi-layer pipeline from raw ingestion to production features.
• Onboard external data sources including credit bureaus and identity providers into the platform.
• Build monitoring systems to detect feature drift, mismatches, and data-quality issues.
• Own data observability, ensuring freshness, completeness, and lineage of shipped features.
• Collaborate with data scientists and ML engineers to turn research logic into robust pipeline code.
• Improve internal tooling, standards, and documentation to accelerate feature shipment.

Requirements

• 2-3 years of experience in data engineering, analytics engineering, or engineering-oriented data analysis.
• Strong proficiency in SQL for writing and optimizing complex queries.
• Solid Python skills for data pipelines and scripting (pandas).
• Hands-on experience with dbt or building similar ETL/ELT pipelines.
• Working understanding of ML concepts, specifically feature engineering and training-serving consistency.
• English: B1 or higher required for communication with an international team.

Nice to have

• Professional background in Risk, credit, lending, or fintech.
• Experience with Snowflake and AWS cloud platform.
• Familiarity with ML model registries and feature stores.
• Knowledge of applied statistics and A/B testing.
• Experience with CI/CD and orchestration for data pipelines.

Culture & Benefits

• Relocation support to hubs in Cyprus, Serbia, Georgia, or Kazakhstan for employees and their families.
• Flexible work arrangements (remote or office-based).
• Comprehensive healthcare coverage.
• Education budget for professional training, certifications, and language lessons.
• Wellness budget for mental health and fitness activities.
• 20 days of annual leave plus paid sick leave.