DWH Team:
Our bank runs on data-driven processes, and the DWH team plays a central role in enabling that. We are responsible for building and maintaining data pipelines from all internal and external sources, developing data marts for reporting and analytics, and creating a toolchain that simplifies working with data across the сompany.
We are looking for an Analytics Engineer for our Risk Domain.
In this role, you will partner directly with business stakeholders and act as a bridge between business and engineering. You will work deeply with risk data (risk engine, credit bureau, payments, risk indicators), building scalable, production-ready solutions on top of our DWH, while contributing to the development of the domain through data modeling, solution design, and close collaboration with business stakeholders.
Challenges that await you:
- Collaborating with Risk domain stakeholders to formalize and translate their data needs into structured ETL requirements
- Decomposing risk-related domains (applications, rules, features, decision logic) into clear and maintainable data models
- Analyzing potential data sources across raw and processed layers to identify optimal integration points
- Designing logical data models and supporting the implementation of scalable ETL pipelines and data marts within the DWH
- Defining and aligning key risk metrics (e.g. DPD buckets, default flags, aggregates) with business stakeholders
- Coordinating and optimizing data flows between risk processes and core DWH components
- Validating and iterating on data solutions together with business users
- Ensuring data solutions are production-ready (scheduling, optimization, maintainability)
- Contributing to the DWH knowledge base by documenting data lineage, transformations, and business rules
- Promoting a strong data culture and proactively contributing to the development of the risk data domain
What makes you a great fit:
- 2-3 years of experience as a Data Analyst/ Analytics Engineer or System Analyst DWH is required
- Strong domain expertise in the Risk or Finance domain
- Knowledge of the data analysis techniques
- Strong hands-on experience with SQL at the level of writing complex queries
- Understanding of data modeling and data warehousing concepts
- Open mind for problem-solving and good troubleshooting skills
- Strong communication and collaboration skills to effectively work with cross-functional teams, including data engineers, analysts, and stakeholders, to deliver high-quality data solutions
- Ability to work independently and as part of a team
- Attention to detail and strong organizational skills
- B1 or higher English level for effective communication with an international team
Our ways of working: