Offers “Allianz”

New Allianz

Financial Data Platform Engineer - GRIPS (m/f/d)

  • München, GERMANY

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

 

 

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