data engineer for financial reporting

The customer is an established financial services provider offering solutions for individuals and organizations focused on long-term financial planning and investment. It combines industry expertise with modern technology to simplify financial processes and improve customer experience, operational efficiency, and access to services. The project is modernizing retail technology and building a secure, scalable, governed enterprise data and analytics platform to transform reporting, integrate data sources, and support regulatory and operational reporting, advanced analytics, data migration, and future strategic data products.

• Lead the design, development, and operationalization of scalable data engineering solutions for the Sunrise programme
• Contribute to the design and implementation of the new data platform, working with the client's architects and Principal Data Engineer
• Design and implement data ingestion pipelines from Sapiens, IRIS, and other enterprise source systems
• Develop ETL/ELT pipelines using Azure Data Factory, Azure Databricks, and Microsoft Fabric
• Build and maintain data solutions across Azure Data Lake and modern cloud data platforms
• Implement medallion architecture and reusable data engineering patterns, using Data Vault for Bronze/Silver and Kimball dimensional modeling for Gold/reporting
• Develop curated datasets, analytical data products, and trusted business views
• Implement data transformation, cleansing, validation, and reconciliation processes
• Support source-to-target integration as Sapiens replaces IRIS; this is new-build integration work, not migration of the existing data engineering framework
• Work with Business Analysts, Data Analysts, Data Architects, the client's Principal Data Engineer, and other engineering teams to translate requirements into production-ready solutions
• Ensure pipelines and data products meet scalability, reliability, performance, security, and data quality requirements
• Implement automated data quality and validation checks across pipelines and datasets
• Support regulatory and operational reporting, including reinsurance extracts and the valuation system feed, ensuring data is accurate, complete, and traceable
• Implement monitoring, logging, and operational controls for pipelines and platform services
• Contribute to CI/CD and DevOps practices using Azure DevOps
• Support pipeline and code-generation automation where appropriate; infrastructure-as-code is owned by a dedicated Platform Engineer
• Develop reusable frameworks, components, and engineering standards to accelerate programme delivery; redesign the current framework
• Contribute to data governance, lineage, metadata, and security requirements, including handling PII in a secured, obfuscated, access-controlled layer
• Work with platform and architecture teams to align solutions with enterprise architecture and governance standards
• Explore and implement AI-enabled approaches to data engineering and SDLC automation
• Support data foundations for future AI and agentic AI use cases; the client already runs a production LLM/data-agent on a separate dataset and wants similar capability here
• Participate in technical design, code reviews, troubleshooting, and production support
• Mentor other engineers and contribute to engineering best practices within the Data Team
• Set engineering patterns and standards

• 6+ Years of commercial Data Engineering experience
• Experience designing a similar greenfield data-platform framework
• Strong hands-on Azure DevOps experience, including YAML pipelines and CI/CD pipeline design
• Strong hands-on experience designing and developing enterprise-scale data pipelines and platforms
• Strong experience with Microsoft Azure data services
• Advanced hands-on experience with Azure Databricks and Apache Spark
• Strong experience with Azure Data Factory
• Practical experience with Microsoft Fabric and modern cloud analytics platforms
• Experience with Azure Data Lake or cloud data storage
• Strong SQL skills and experience with relational and analytical data
• Experience with ETL/ELT development and data integration patterns
• Strong understanding of medallion architecture and modern data platform design
• Familiarity with Data Vault and Kimball dimensional modeling; dedicated data modeling experience is not required
• Experience designing scalable, reusable, production-ready data engineering frameworks, ideally from scratch rather than only extending existing conventions
• Experience with data quality, validation, reconciliation, and monitoring
• Experience with CI/CD and DevOps practices, preferably using Azure DevOps
• Understanding of data governance, metadata, lineage, security, and access control
• Experience in Agile delivery environments
• Strong problem-solving and analytical skills
• Ability to work effectively with Business Analysts, Architects, Data Analysts, and other technical stakeholders
• English at Intermediate+ level or above
• Будет плюсом: Associate certification, Microsoft Fabric Data Factory, Lakehouse or Fabric Data Engineering, Sapiens or similar core enterprise/business systems, migration from legacy reporting platforms to modern cloud data platforms, experience in Retail, Financial Services, Insurance or other regulated industries, regulatory reporting and audit requirements, Data Mesh or enterprise data platform implementations, event-driven or real-time data integration, AI-assisted software engineering or agentic AI solutions, integrating AI tooling into requirements, coding, testing, documentation or deployment, infrastructure-as-code and cloud automation, Power BI or other enterprise BI/semantic modelling technologies

• The opportunity to change the project and/or develop expertise in an interesting business domain
• Professional, financial, and career growth; mentoring and onboarding systems for each new employee
• Opportunity to earn up to an additional 1,000 EUR per month depending on expertise, included in the annual bonus, by participating in company activities
• Access to the corporate training portal and its continuously updated knowledge base
• Corporate events and amenities, including parties, pizza days, PlayStation, fruit, coffee, snacks, and movies
• Certification compensation (AWS, PMP, etc.)
• Referral program
• Private health insurance and sports compensation, depending on the type of employment
• Work is available from Austria, Belgium, Bulgaria, Croatia, Cyprus, Czech Republic, Denmark, Estonia, Finland, France, Germany, Hungary, Italy, Latvia, Lithuania, Luxembourg, Poland, Portugal, Romania, Slovakia, Slovenia, Spain, Sweden, The Netherlands, or the United Kingdom