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We are looking for an Analytics Engineer to join Sii and a strategic project delivered for a Copenhagen-based fintech company. In this role, you will build and scale business-critical data models that drive decision-making across key domains such as credit, payments, and fraud/AML.
You will operate in an environment with high engineering standards (CI/CD, code reviews, data governance) and work on high-impact data products where reliability, ownership, and operational discipline are essential. This role involves collaboration across multiple domains and stakeholders, offering the opportunity to broaden your expertise while working on complex, real-world data challenges.
Your tasks
Build and maintain core data models in dbt that power critical reporting and decision-making in credit, payments, and fraud/AML
Partner closely with business stakeholders, Data Engineers, and Data Analysts to define requirements, clarify ownership, and align on success criteria
Work collaboratively with both technical and non-technical stakeholders, translating complex or ambiguous business logic into scalable data solutions
Contribute to the semantic layer (LookML) to ensure consistent, scalable reporting and enable self-service analytics across multiple domains
Take ownership of data quality, implementing testing, monitoring, and documentation; proactively detect and resolve issues in business-critical data pipelines
Support reliable data workflows, including working with orchestration tools such as Airflow/Astronomer where needed
Contribute to and uphold strong analytics engineering practices, including code reviews, reusable patterns, and reducing technical debt
Balance work across multiple data domains and shared definitions, which requires adaptability and effective context switching
Requirements
Min. 5 years of hands-on experience with dbt and modern cloud data warehouses (BigQuery)
Proficiency in SQL skills and experience building well-structured, reusable models in a layered architecture
Ability to translate unclear or messy business requirements into clean, performant, and maintainable data transformations
Familiarity with Git-based workflows, version control, and CI/CD practices in analytics engineering environments
Strong sense of ownership and accountability, especially when working with business-critical data products
Comfort working in environments with high engineering and governance standards
Strong collaboration and communication skills, with the ability to engage proactively with stakeholders beyond data teams
Interest in developing expertise across domains such as payments, credit, and fraud/AML, rather than focusing narrowly on a single area
Ability to communicate effectively in English in an international environment
Fluent Polish required
Residing in Poland required
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