Join a dynamic team at the pulse of global markets, where we deliver innovative software and service solutions for essential financial reporting and capital markets transactions. At DFIN, we are a values-driven organization that empowers you to build a fulfilling career while bringing your authentic self to work every day. Our "Win as One" mentality ensures that our team's success is directly linked to Client, Shareholder and Employee Satisfaction. Recognized as one of AMERICA'S MOST LOVED WORKPLACES® for five consecutive years and a Built In Best Places to Work for six years, we are committed to our employees' total well-being. Enjoy competitive compensation, a flexible workplace, comprehensive benefits, and opportunities for professional growth. Bring your passion and talents to DFIN - because being YOU thrives here. Summary: We are looking for technical leaders at all levels who want to push the boundaries of data architecture to deliver best in market SaaS solutions. We offer a challenging environment where you will have to grow, adapt and build the foundation for our next generation of data products. Our customers rely on us in the moments that matter. Engineering delivers on that promise. We are hiring a Principal Data Platform Engineer to turn established data architecture into reliable, production-grade systems . This is a builder role , not a conceptual architect position. The Principal Data Platform Engineer is responsible for implementing and institutionalizing our data platform patterns-ingestion, modeling, data quality, and reliability-across products and teams. You will work closely with the Senior Director, architects and product engineering teams, translating architectural intent into repeatable, enforceable, and observable solutions . This role exists to ensure that our data strategy operates predictably at scale . Responsibilities: - Lead the design and implementation of a Medallion architecture on Azure Fabric, enabling efficient flow from raw to curated data. - Develop clear, well‑tested, and well‑documented code in Python/PySpark and SQL, following modern DataOps best practices. - Optimize Lakehouse performance using partitioning, indexing, and effective OneLake storage strategies to support large regulatory datasets. - Analyze real business problems and deliver pragmatic data solutions, keeping strategy grounded and execution focused. - Collaborate with product managers, developers, SREs, and engineers across levels and geographies to build high‑impact software. - Design systems with operability in mind, using monitoring and metrics to quickly diagnose pipeline failures and data quality issues. - Champion simplicity, reliability, manageability, scalability, extensibility, reusability, and performance. - Continuously identify and address technical debt, making it visible and resolving it proactively. Qualifications: - Be committed to your professional development, the data products you deliver, and the firm. - Demonstrated experience with modern Data Lakehouse architectures; hands‑on experience or strong knowledge of Microsoft Fabric, OneLake, and Delta Lake (Parquet) is highly preferred. - 8-10 years of experience designing and building scalable, data‑centric applications and distributed data systems. - Proven experience developing secure data pipelines that meet enterprise security standards and participating in financial systems security practices. - Strong proficiency in Python/PySpark, SQL, and Fabric Data Factory (or Azure Data Factory). - Nice to have: experience with Azure, AKS, Docker, Kubernetes, and Power BI semantic models. - Bachelor's degree in Computer Science or equivalent practical experience. It is the policy of Donnelley Financial Solutions to select, place, and manage all its employees without discrimination based on race, color, national origin, gender, age, religion, actual or perceived disability, veteran status, actual or perceived sexual orientation, genetic information or any other protected status. If you are a qualified individual w ith a disability or a disabled veteran, you have the right to request a reasonable accommodation if you are unable or limited in your ability to use or access jobs.dfinsolutions.com as a result of your disability. You can request a reasonable accommodation by sending an email to talentacquisition@dfinsolutions.com . At DFIN, protecting your identity is a top priority. Please be aware of scammers impersonating DFIN recruiters. DFIN recruiters will never request personal information via email or text. You will only receive a text from us if you've already been in contact. All automated messages will come from talentacquisition@dfinsolutions.com . If you ever have doubts about the legitimacy of any communication from us, please do not hesitate to reach out for verification via talentacquisition@dfinsolutions.com (this email is for general TA questions and is not used for updates on your application status). #BI-Remote

• Projektowanie i rozwój pipeline’ów danych oraz rozwiązań przetwarzania danych w oparciu o Azure Databricks i Python • Budowa i utrzymanie rozwiązań na platformie Azure Data (Data Lake, Data Factory, Synapse) • Tworzenie i rozwój Data Products oraz zarządzanie nimi (Unity Catalog) • Współpraca z biznesem — zbieranie wymagań i przekładanie ich na rozwiązania techniczne • Dbanie o jakość danych, bezpieczeństwo oraz zgodność z wymaganiami • Integracja rozwiązań danych z innymi systemami w organizacji • Usprawnianie wydajności, skalowalności i kosztów rozwiązań

• Design, build, and maintain data pipelines that ensure reliable data flow from source systems through transformation layers to reporting • Integrate data quality checks and validation into the pipeline workflow • Implement error handling, logging, and retry capabilities to keep pipelines robust and recoverable • Develop SQL and Python-based transformations that cleanse, enrich, and structure data for analytical use • Monitor and tune pipeline and query performance • Collaborate with your scrum team and cross-functional partners across analytics, product, and engineering

• supporting the development, maintenance, and optimization of data pipelines and analytics-ready datasets • collaborating across multiple teams and stakeholders to solve complex problems and support data-driven initiatives • build, maintain, and optimize data pipelines utilizing Azure Data Factory • implement monitoring, alerts, and testing of data pipeline performance, data quality metrics, and lineage • troubleshoot data issues and perform root cause analysis • collaborate with analysts, stakeholders, and product owners to translate business needs into data requirements • support deployment and operationalization of machine learning models • continually improve ongoing reporting and analytics