Descripción de la oferta
Experteer Overview
In this role you will design and own the data infrastructure powering credit risk management, exposure monitoring, and decision-making across customer, account, and transactional data. You will collaborate with the Credit Data Scientist, Credit Management leadership, and regional credit teams to build reliable data foundations for analytics, ML models, and management reporting. You contribute to strong credit governance by delivering scalable data products and proactive risk insights across regions. This is a hands-on engineering role with a clear impact on credit decisions and process improvement.
Compensaciones / Beneficios
• Design, develop, and maintain data pipelines and transformation models in Snowflake to support credit monitoring, portfolio reviews, and downstream analytics and ML
• Build and govern the credit data warehouse layer: joins, unions, business rules, slowly-changing dimensions, and curated marts on top of SAP-landed data and external sources
• Implement a transformation framework (dbt or equivalent) with tests, documentation, and version control to ensure data quality, lineage, and modularity of credit transformations
• Orchestrate and monitor pipelines so that downstream consumers (analysts, ML models, Power BI) receive reliable, on-time data — with proper scheduling, alerting, and error handling in place
• Onboard new data sources — credit insurance feeds, financial information providers, local insolvency registries, and the customer portal — into the credit data platform
• Drive a data quality framework: freshness, uniqueness, referential integrity, and anomaly detection on critical credit datasets
• Collaborate with global and regional credit stakeholders, the Credit Data Scientist, and the Credit Data Analyst to translate business and policy requirements into well-modeled data products
• Support the productionisation of credit risk models, scoring approaches, and early warning indicators by providing the upstream features, pipelines, and orchestration they depend on
• Demonstrate autonomy in technical execution and delivery of engineering tasks and projects, while aligning with strategic direction from Credit leadership and contributing to a collaborative team environment
Responsabilidades
• 3 to 5 years of relevant work experience in data engineering, analytics engineering, or a similar role
• Bachelor's Degree in Computer Science, Engineering, Big Data, or related field required
• Strong proficiency in SQL (advanced — window functions, CTEs, query optimization)
• Solid working knowledge of Python for data engineering tasks (pipelines, scripting, data quality)
• Hands-on experience with a cloud data warehouse — Snowflake strongly preferred
• Working understanding of dimensional data modeling and ETL/ELT patterns
• Hands-on experience working with ERP-sourced financial data (SAP preferred)
• Experience with Git and standard collaborative development practices (branching, code review, versioning)
• Strong analytical mindset, attention to detail, and problem-solving skills
• Excellent communication skills in English; additional languages are an advantage
• Ability to work effectively in a global, multicultural environment
• Comfortable working independently, managing multiple priorities, and translating business needs into engineering outcomes
Requisitos principales
• Hybrid work model
• Career growth programs
• Health insurance
• Paid leave
• Retirement plans
