Eleving Group is a fast-growing international fintech company specializing in vehicle and consumer finance, operating a multi-brand portfolio in 17 countries across 3 continents, with a 4300+ strong team. As pioneers in emerging economies, we’re driving change, encouraging financial inclusion and upward social mobility through innovative, easy-to-use financial products.

Strive for a way-way up with the Eleving

At Eleving, we're building financial products on top of real data - credit scoring, risk models, and real-time decisioning. We're not a company where data sits in a warehouse waiting to be used. It sits at the center of every product decision we make.

We're looking for a Data / ML Engineer who takes ownership of the full lifecycle: from reliable pipelines to production-grade model deployment, with the monitoring and traceability to back it up.

What you'll own

• Design, build, and maintain scalable data pipelines for ingesting, transforming, and processing volumes of data - with a bias toward real-time over batch where it matters
• Deploy and operationalize machine learning models alongside data scientists, owning reliability and performance post-launch
• Drive AI initiatives end-to-end: from architecture decisions to implementation
• Implement data quality checks, governance practices, and compliance controls
• Keep infrastructure resilient — fault-tolerant, observable, and maintainable
• Bring an AI-native approach to your own work, using agentic coding tools as a force multiplier

What you'll bring

• 2–5 years in data engineering, ML engineering, or a closely related software engineering role
• Strong Python; solid SQL
• Experience building and running data pipelines in cloud environments (AWS, GCP, or Azure)
• Hands-on with Docker; comfortable with containerized deployments
• Familiarity with ML frameworks (Scikit-learn, tree boosting methods, or similar)
• Understanding of data modeling - dbt or equivalent
• Comfortable using AI-assisted development tools (Cursor, Copilot, or similar) as a standard part of your workflow
• A degree in Computer Science, Data Engineering, or a related field is a good signal, but demonstrable experience matters more to us

Bonus points for

• MLOps practices: CI/CD for models, experiment tracking (MLflow, DVC)
• Real-time streaming experience - Kafka, Kinesis, or similar
• Data warehousing and ETL tooling (Vertica, Pentaho, or similar)
• Infrastructure-as-code (Terraform or equivalent)
• Experience in fintech - credit scoring, fraud detection, or risk modeling
• Kubernetes or broader orchestration experience

What we offer

• Monthly gross salary starting from €3000, based on your experience and qualifications
• Health insurance from Day 1
• Performance-based bonus
• Hybrid work & flexible working with 3 days a week from our Riga office
• A team that builds real things with real data - no toy projects
• Support for learning & development