Principal Data Platform Engineer

Principal Data Platform Engineer

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.

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).
• 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.