Cloud Data Architect

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’re seeking technical talent who are driven to challenge themselves and deliver best‑in‑market SaaS solutions. You’ll join a fast‑paced, collaborative environment that encourages growth, adaptability, and continual skill development. Your impact will be tangible as we build innovative solutions for the moments that matter most to our customers.
The Cloud Data Architect is responsible for delivering results for the Engineering department by: 
•    Envisioning the data architecture required to deliver our best of class products into a SaaS environment  
•    Ensuring that data is secure, fast, modeled, accessible and works with the software. 
•    Being a leader at DFIN who is both highly technical but also business savvy 
•    Actively participating in the engineering process- anticipating our future needs  

Responsibilities:

Set Standards on Data Usage 
•    Set, communicate, and govern technical standards throughout the product development organization. This includes the standards for the data architecture itself and working closely with our delivery teams in setting standards of how the work gets done. 
Advance our Cloud Data Architecture 
•    Drive the creation and implementation of architecture standards and artifacts Collaborate with the Engineering team to develop the architecture, build the backlog, and adjust the design as necessary. Collaborate with the Product Management and Engineering Leadership team to make sure the voice of data architecture is part of our SaaS architecture. 
•    Solve difficult data modeling, optimization, location and other problems. 
•    Analyze the risks, benefits, and opportunities associated with the implementation of a solution. 
Be Diligent about Planning and Design 
•    Translate product requirements to system level architecture and high-level designs. Work with senior technical team (technical leads, principal engineers, etc.) to develop detailed designs. 
Have a Flexible mindset 
•    Delivers solutions in small steps, with incremental feedback loop from internal and external stakeholders. Flexible and able to adjust or change direction as the business environment and technology universe evolves and changes.

Qualifications:

•    Advanced proficiency in SQL for query optimization and analytics (e.g., on Azure Synapse, Oracle, or Snowflake). 
•    Familiarity with cloud platforms (e.g., Azure, OCI) and tools like Azure Data Factory, Databricks, or Apache Airflow.   
•    Expert in data strategy - creating and managing a platform data approach
•    Design scalable data architectures aligning with business goals. 
•    Implement data governance, security, and compliance frameworks. 
•    Optimize data pipelines for performance and cost-efficiency. 
Experience Level: 7–10+ years of experience in data engineering, architecture, or related roles, with a focus on cloud and big data technologies. 
Certifications: Highlight relevant certifications like Microsoft Certified: Azure Data Engineer Associate, Databricks Certified Associate Developer for Apache Spark, or Certified Data Management Professional (CDM) 
Nice to have: 
•    Hands-on experience with data lakes (e.g., Azure Data Lake Storage, Delta Lake) and lakehouse architectures. 
•    Expertise in DataBricks and/or Apache Spark (PySpark, Spark SQL) for distributed data processing. 
•    Strong Python skills for scripting, automation, and pipeline development. 

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. 

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