Senior Data Architect

Why Ryan?

• Global Award-Winning Culture

• Flexible Work Environment

• Generous Paid Time Off

• World-Class Benefits and Compensation

• Rapid Growth Opportunities

• Company Sponsored Two-Way Transportation

• Exponential Career Growth

Job Description

The Senior Data Architect is responsible for overseeing the implementation of technical solutions for the ingestion, transformation, processing, and storage of data in high-volume, low-latency pipelines. This role requires an enterprise mindset to build robust, high-performance technology solutions.

The Senior Data Architect position combines strong hands-on technical leadership with the management of matrixed resources to achieve business outcomes. This role is expected to be equally engaged in developing code and developing the skills and competencies of the broader team.

People

• Model and design the data platform architecture—defining data domains, data flows, and platform topology within a lakehouse environment such as Databricks—while leveraging a variety of tools and languages to build and maintain data pipelines within the Platform Reference Architecture.

• Work directly with management, product teams, and practice personnel to understand their platform data requirements, translating them into well-structured platform data models and analytical frameworks that reflect the intended data platform design.

• Maintain a positive work atmosphere by behaving and communicating in a manner that encourages productive interactions with customers, co-workers, and supervisors.

• Develop and engage with team members by creating a motivating work environment that recognizes and rewards strong performance while holding team members accountable.

• Foster an innovative, inclusive, and diverse team environment, promoting a positive team culture, encouraging collaboration and self-organization, and delivering high-quality solutions.

Client

• Collaborate on an Agile team to design, develop, test, implement, and support highly scalable data solutions on lakehouse platforms such as Databricks, with particular emphasis on platform data modeling, data flow analysis, and ensuring solutions reflect sound data architecture principles.

• Collaborate with product teams and clients to deliver robust cloud-based data solutions that drive tax decisions and provide powerful experiences, leveraging data analysis and platform modeling to ensure data is accurate, well-governed, and business-ready.

• Analyze user feedback and activity and iterate to improve services and the user experience.

Value

• Secure data in alignment with internal information and data security policies, best practices, and client requirements.

• Create and implement robust cloud-based data solutions that scale effectively, underpinned by well-designed platform data models and analytical frameworks—including medallion architecture (Bronze/Silver/Gold) and Delta Lake patterns—that provide powerful experiences for both internal teams and clients.

• Perform unit tests and conduct reviews with other team members to ensure solutions are rigorously designed, elegantly coded, and effectively tuned for performance, including formal platform architecture reviews to validate data flows and platform design against business requirements and enterprise standards.

• Stay current on technology trends, experiment with and learn new technologies, participate in internal and external technology communities, and mentor other members of the engineering community, with a focus on advancing data platform modeling and analytics capabilities across the practice.

• Perform other duties as assigned.

Education and Experience

• Bachelor’s or master’s degree in a related field.

• Ten (10) or more years of experience developing data technologies, with significant depth in data platform modeling, including defining data domains, data products, information flows, and platform reference architectures on lakehouse platforms such as Databricks, including Delta Lake, Unity Catalog, and medallion architecture design.

• Ten (10) or more years of experience deploying extract, transform, and load/extract, load, and transform (ETL/ELT) solutions in production environments, preferably using Spark-based platforms such as Databricks, with strong proficiency in data analysis and profiling to inform platform design decisions and support reporting needs.

• Ten (10) or more years of experience developing cloud-based data services, preferably in Amazon Web Services (AWS) or Microsoft Azure, with emphasis on data governance, metadata management, and data catalog practices within lakehouse platforms such as Databricks Unity Catalog.

• Ten (10) or more years of experience developing and overseeing the development of Python, Scala, Java, .NET, or similar solutions—including PySpark and Databricks notebooks—combined with strong SQL skills and experience with business intelligence (BI) and reporting tools such as Power BI and Tableau to support analytical deliverables.

• Ten (10) or more years of experience with database and query tuning, including experience in data quality assessment, data profiling, and establishing data standards to ensure accuracy and consistency across data assets.

• Ten (10) or more years of experience in mixed Windows/Linux environments, with demonstrated ability to partner with business stakeholders to define data requirements, validate data definitions, and deliver analytical insights.

Additional Required Skills and Experience

• Proven track record of exceeding goals and evidence of the ability to consistently make sound decisions through a combination of analysis, experience, and judgment.

• Fluency in one or more database technologies; experience with relational and NoSQL databases is preferred.

• Fluency with distributed data platforms, with hands-on experience using Databricks, including Delta Lake, Unity Catalog, Databricks Workflows, and the Databricks lakehouse architecture, and proficiency with data architecture and platform design tools such as LeanIX, Ardoq, or similar enterprise architecture tools.

• Knowledge of at least one artificial intelligence/machine learning (AI/ML) pipeline technology or platform, along with familiarity with statistical analysis and data visualization to translate findings into clear business recommendations.

• Experience deploying, monitoring, and maintaining data pipelines in production environments—including Databricks Workflows and Delta Live Tables—with familiarity with data governance frameworks, data lineage documentation, and enterprise data catalog tools.

• Design models of the data platform that implement the intended business architecture, including data domains, data products, and information flows within a lakehouse paradigm such as medallion architecture on Databricks.

• Develop diagrams representing key platform components, data flows, and system interactions across the data platform landscape.

• Generate a list of components needed to build the designed platform, including data definitions, integration points, and analytical requirements needed to support the platform architecture.

• Communicate clearly, simply, and effectively.

Computer Skills

To perform this job successfully, an individual must have intermediate knowledge of Microsoft Project, Word, Excel, Access, PowerPoint, Outlook, and Internet navigation and research.

Supervisory Responsibilities

Requires supervisory responsibilities, including training employees, assigning work, and assuring quality throughout deliverables.

Work Environment

• Standard indoor working environment.

• Occasional long periods of sitting while working at a computer.

• Position requires regular interaction with employees at all levels of the Firm and interaction with external vendors as necessary.

• Independent travel requirement: As needed

Equal Opportunity Employer: disability/veteran