Financial Data Platform Engineer GRIPS M F D

Job description

103055 | IT & Entwicklung | Berufserfahren | keine Angabe | IDS | Vollzeit | Dauerhaft JOB PURPOSE/ROLE Join the team behind GRIPS — Group Risk Parameters — one of the key analytics platforms within Allianz Group for yield curves and related financial risk parameters. GRIPS transforms complex market and pricing data into high-quality, reliable investment insights used by risk experts, portfolio managers, and decision makers across Allianz Group. As a Financial Data Platform Engineer, you will play a key role in developing, modernizing, and operating GRIPS end to end, covering data pipelines, data marts, APIs, core data assets, and application services. Your work will help ensure that time-critical financial information remains accurate, traceable, performant, and available for downstream systems and business-critical decisions. Beyond implementation, you will have the opportunity to act as a solution-oriented owner, actively shaping the platform architecture, strengthening engineering quality, and evolving a data-intensive environment together with business analysts, developers, and quantitative experts. You will translate financial, analytical, and regulatory requirements into scalable data solutions and contribute to a modern platform that combines operational robustness with innovation, automation, and long-term maintainability. This role also offers the opportunity to shape the future of GRIPS by exploring and implementing AI-driven solutions, automation approaches, and advanced analytics capabilities in a highly data-intensive environment. KEY RESPONSIBILITIES Develop, maintain, and optimize GRIPS database schemas in Oracle Database and PL/SQL, including bitemporal historization, market data interfaces, and interfaces to downstream consumer applications. Develop and maintain the internal GRIPS Python application, including the user interface, orchestration framework, and related backend services. Design, build, and operate reliable ETL pipelines, data marts, and API-based data interfaces for complex financial and market data. Take end-to-end ownership for solution design, implementation, operation, and continuous improvement across the GRIPS platform landscape. Evolve and modernize existing components into efficient, maintainable, and future-ready Python and PL/SQL-based solutions with a strong focus on performance, stability, and long-term platform quality. Collaborate closely with clients, business analysts, developers, and quantitative experts to translate financial and regulatory requirements into scalable technical solutions. Define and apply software development best practices across the full delivery lifecycle, including clean code, testing, documentaion, CI/CD, and operational readiness. Support operational and analytical initiatives such as historical time-series recalculations, data quality improvements, and platform performance optimization. Identify and implement AI-driven solutions, automation opportunities, and advanced analytics capabilities that create measurable value for GRIPS and its users. KEY REQUIREMENTS/SKILLS/EXPERIENCE Technology Stack Core engerneering: Python, Oracle Database, SQL, PL/SQL, data modelling, clean code, and software architecture Data platform: ETL pipelines, data marts, market data integration, large financial datasets, bitemporal data structures, and data quality frameworks Integration and operations: REST APIs, Apache Airflow, CI/CD, Git, Linux, Docker, and cloud or container-based environments Innovation layer: automation, advanced analytics, machine learning, and AI-driven solution approaches Required University degree in Computer Science, Mathematics, Finance, Engineering, or a comparable field Several years of professional experience in software engineering, data engineering, or the development of data-intensive applications Strong hands-on experience with relational databases, SQL, and database concepts; experience with Oracle and PL/SQL is highly relevant Solid understanding of data modelling, data transformation, and reliable data pipelines or analytical data platforms Ability to design maintainable solutions and contribute to architecture decisions in a complex, business-critical platform environment Structured, solution-oriented working style with strong ownership, communication skills, and the ability to translate business requirements into scalable technical solutions Interest in financial markets, risk parameters, and investment data; extensive quantitative finance knowledge is not required Fluent in English; German language skills are a plus Desired Experience with financial market data, pricing data, valuation concepts, or regulatory reporting Practical experience with Python or comparable programming languages, REST APIs, Apache Airflow, Docker, Linux, cloud platforms, or container-based environments; Python is ideal Knowledge of C++, QuantLib, Python/C++ integration patterns, or similar quantitative and analytical technology stacks Interest in applying machine learning, AI, and advanced analytics to real business and data platform challenges