Data Architect / Snowflake Expert

Seine Client is seeking an experienced Data Architect / Snowflake Expert to join our Technology Practice and support a strategic client engagement focused on modernizing legacy tax management and tax preparation systems used to serve corporate customers., The selected candidate will work closely with Seine Client leadership, customer stakeholders, business analysts, tax subject matter experts, offshore development resources, and technical delivery teams to define the target-state data architecture, establish data and analytics best practices, and help deliver modernized solutions that improve automation, data quality, reporting, tax workflow efficiency, and operational visibility., The Data Architect / Snowflake Expert will be responsible for leading architecture, design, and hands-on implementation activities across the modernization program., * Lead current-state assessment and target-state architecture for legacy tax management, tax preparation, reporting, workflow, data integration, and analytics environments.

• Design scalable Snowflake-based data architecture for structured, semi-structured, and unstructured tax-related data.

• Define Snowflake data architecture standards, data models, data mappings, transformation rules, governance patterns, and reusable data services.

• Architect and implement Snowflake solutions that support tax data management, reporting, analytics, document processing, and operational automation.

• Provide both architecture best-practice guidance and hands-on delivery support for complex data pipelines, data models, analytics workloads, and production-critical components.

• Design and implement Snowflake Cortex use cases involving AI functions, document intelligence, LLM-powered summarization, classification, extraction, search, entity recognition, and analytics automation.

• Support use cases involving tax workpapers, supporting documents, legacy tax data, filings, notices, reports, calculations, and audit-supporting records.

• Establish best practices for Snowflake security, role-based access control, data governance, data quality, lineage, performance optimization, cost management, CI/CD, monitoring, and operational support.

• Partner with tax business stakeholders to understand tax data flows, calculations, compliance needs, reporting requirements, source system dependencies, and operational pain points.

• Translate business and tax-domain requirements into scalable data, analytics, AI, and application architecture.

• Support modernization of manual, spreadsheet-driven, document-heavy, or legacy tax processes into governed, automated, supportable platform capabilities.

• Lead data architecture reviews, data model reviews, technical walkthroughs, code reviews, integration reviews, and delivery quality checkpoints.

• Manage and mentor a small team of offshore technical resources when needed, including task planning, technical guidance, quality review, and delivery coordination.

• Support data validation, testing, defect triage, migration planning, release planning, deployment, cutover, production stabilization, and knowledge transfer.

• Create and maintain architecture deliverables, including solution blueprints, data models, source-to-target mappings, transformation specifications, Snowflake design patterns, Cortex use case designs, technical decision logs, and operational runbooks.

• Identify technical risks and recommend mitigation strategies related to legacy systems, data quality, performance, security, scalability, integration complexity, AI governance, and delivery timelines.

• Collaborate with integration teams using ETL, ELT, API, or iPaaS platforms, including MuleSoft Anypoint Platform where applicable.

• Enterprise data architect and hands-on implementation leader

• Legacy tax management, tax preparation, reporting, workflow, data integration, and analytics environment*

• • Hands-on experience with SQL, Snowflake data modeling, stored procedures, views, tasks, streams, dynamic tables, Snowpark, and data pipeline implementation

• Practical Python experience preferred, especially for data engineering

• Strong understanding of data security, This role requires a senior technology professional who can operate as both an enterprise data architect and hands-on implementation leader. The ideal candidate will bring deep Snowflake expertise, strong data architecture experience, and specific hands-on knowledge of Snowflake Cortex capabilities for AI-enabled analytics, document intelligence, data enrichment, summarization, classification, search, and automation., Candidate should be comfortable with enterprise tax automation, data transformation, analytics, tax engine optimization, document-heavy workflows, AI-enabled insights, and real-time reporting. This role is highly aligned to legacy tax platform modernization, data consolidation, AI-enabled tax operations, governed analytics, and enterprise data platform transformation., * Bachelor's degree required, preferably in Computer Science, Information Systems, Engineering, Data Management, Analytics, or a related technology field.

• Minimum 10 years of professional experience in data architecture, enterprise data platforms, data engineering, analytics architecture, enterprise application modernization, or complex platform implementation.

• Deep hands-on experience with Snowflake in enterprise production environments.

• Proven experience designing and implementing Snowflake-based data platforms, data warehouses, data lakes, data marts, analytics layers, and governed data models.

• Specific hands-on experience with Snowflake Cortex, including one or more of the following:

• Cortex AI Functions

• Cortex Analyst

• Cortex Search

• Document intelligence

• LLM-enabled data enrichment

• Summarization

• Classification

• Entity extraction

• Document parsing

• Natural language analytics

• AI-enabled workflow automation

Strong understanding of modern data architecture patterns, including data ingestion, transformation, semantic modeling, data governance, data quality, metadata management, and consumption-layer design.

Hands-on experience with SQL, Snowflake data modeling, stored procedures, views, tasks, streams, dynamic tables, Snowpark, and data pipeline implementation.

Practical Python experience preferred, especially for data engineering, automation, AI/ML, or Snowflake Cortex-related use cases.

Ability to design and implement secure, scalable, reusable, and supportable data and analytics solutions.

Experience defining data models, mapping rules, transformation logic, canonical data structures, validation rules, and data reconciliation approaches.

Experience working across the full delivery lifecycle, including discovery, architecture, design, build, test, deployment, stabilization, and support transition.

Strong understanding of data security, role-based access control, encryption, privacy, auditability, logging, monitoring, and production support practices.

Ability to communicate effectively with executive stakeholders, business users, tax subject matter experts, enterprise architects, developers, testers, data engineers, and offshore delivery teams.

Demonstrated ability to provide technical leadership while also contributing directly to hands-on implementation work.

Experience leading, mentoring, or coordinating small technical teams, including offshore resources.

Strong consulting mindset with the ability to work in a client-facing environment, manage ambiguity, and deliver practical solutions.

The following preferred qualifications are highly desirable:

• Snowflake certifications are preferred, especially:

• SnowPro Core

• SnowPro Advanced: Architect

• SnowPro Advanced: Data Engineer

• SnowPro Specialty: Gen AI

Demonstrated experience designing and implementing Snowflake Cortex solutions in a real business environment.

Experience with Snowflake AI Data Cloud, Snowpark, Streamlit in Snowflake, Snowflake Marketplace, data sharing, and enterprise data governance.

Experience building AI-enabled analytics or document intelligence solutions for finance, tax, compliance, audit, legal, or other document-intensive business areas.

Experience with financial tax systems, corporate tax reporting, tax preparation platforms, tax workflow automation, direct tax, indirect tax, tax engines, tax provision, or tax data management.

Experience with tax platforms or related ecosystems such as ONESOURCE, Vertex, Domo, ERP tax modules, financial reporting systems, or custom tax applications.

Experience modernizing legacy systems, manual workflows, spreadsheet-based processes, fragmented data environments, or aging reporting platforms.

Experience in professional services, consulting, advisory, financial services, accounting, or compliance-sensitive environments.

Experience with ETL, ELT, and enterprise integration technologies.

Experience with MuleSoft Anypoint Platform is an added plus.

Experience with REST APIs, file-based integrations, database integrations, enterprise application connectors, event-driven patterns, and batch data exchange is a plus.

Experience with CI/CD pipelines, DevOps, automated testing, source control, deployment automation, and release governance.

Experience working with distributed teams across the U.S. and offshore delivery centers.

Ideal Candidate Profile

The ideal candidate is a data architect who can comfortably move between strategy, architecture, and implementation. This person should be able to lead a design session with business and tax stakeholders in the morning, review Snowflake data architecture and Cortex design patterns with developers in the afternoon, and troubleshoot a complex data transformation, performance issue, or production support concern when needed.

The best candidate will have:

• Strong Snowflake architecture and implementation depth.
• Practical hands-on Snowflake Cortex experience.
• Strong data architecture, data engineering, and analytics design skills.
• Confidence working with business and tax stakeholders.
• Ability to simplify complex legacy environments.
• Strong hands-on technical credibility.
• Experience leading small, distributed teams.
• A consulting mindset focused on client outcomes.
• The discipline to build reusable, governed, well-documented data assets rather than one-off point solutions.
• The ability to bridge legacy tax systems, modern cloud data architecture, AI-enabled analytics, and operational business needs.