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Salary: EUR 70,000 - 80,000 / annual
Solaris is Europe's leading embedded finance platform and fully licensed German bank, pioneering Banking-as-a-Service. The company enables fintechs, digital ecosystems, and multinationals to embed accounts, cards, lending, and payments directly into their products. Solaris is transitioning into an AI-native banking platform with technology infrastructure based in Berlin and banking operations in Frankfurt.
In this Senior Bank Analytics Engineer role, you will design and implement robust, clean, and reusable data models for Risk, Regulatory Reporting, and Finance functions. You'll centralize reporting of financial instruments (credit cards, loans, bonds, deposits) following BIRD and IReF standards. Key responsibilities include:
• Define process steps and tasks to fulfill CoRep (Credit Risk, Market Risk, Operational Risk), FinRep (Balance Sheet, income statements using IFRS and HGB), and Liquidity Reporting (LCR, NSFR) in close collaboration with Risk, Regulatory Reporting, and Finance teams.
• Manage standardized metrics through a semantic layer to serve as single points of truth across reporting, data exploration, and business intelligence.
• Build scheduled matching programs for reconciliation automation to cross-verify the bank's internal ledgers.
• Implement and maintain efficient incremental loading strategies for high-volume, time-series financial data.
• Contribute to the common data quality framework by applying patterns and tests.
• Document processes and technologies, enabling knowledge sharing across teams.
You will work in a fast-paced, regulated environment where your responsibilities and scope will scale with your experience level. The role emphasizes continuous learning, AI-native thinking, and collaboration across technical and non-technical stakeholders.
REQUIREMENTS:
• Degree in Mathematics, Informatics, Natural Sciences, Finance, or Economics.
• Minimum 6 years of experience as an analytics engineer, data analyst, or reporting specialist in a fast-paced, regulated industry.
• Advanced data modeling and data-warehouse development skills.
• Knowledge of cloud data providers and modern data architectures, ideally Snowflake.
• Proficient SQL and Python programming skills.
• Good knowledge of data transformation and orchestration tools, ideally dbt and Airflow.
• Solid understanding of software engineering principles, including version control (Git), CI/CD, and automated testing.
• Very good data visualization skills, ideally Tableau.
• Banking & Domain Expertise: Understanding of double-entry bookkeeping, credit facilities, on/off-balance-sheet items, integrated reporting frameworks, banking standard taxonomies (COREP/FINREP mapping), and ability to translate regulatory requirements into programmatic logic.
• Very strong communication skills for both technical and non-technical audiences.
• Ability to grasp new business concepts and translate them into technical requirements.
• Excellent documentation and knowledge-sharing skills.
• Adaptability and continuous learning mindset.
• Strong negotiation, empathy, and consensus-building abilities.
• Strategic thinking with sense of business criticality and prioritization.
• Ability to mentor and inspire team members.
• Excellent English language skills; German is a plus.
• Comfort with AI tools, critical thinking about AI outputs, and commitment to responsible AI use.
