Data Architect

• Role: Data Architect
• Location: Remote EST
• Duration: 6 Month CTH

• The architect establishes the semantic and canonical data layers and the reusable data constructs that underpin
• ConnectWise's enterprise AI development, and sets the standards that data engineering, business applications,
• and integration teams build against. This is a hands-on architect — not solely a "drawer" of models: the individual
• is accountable for the blueprint and standards (the "what" and "why" of enterprise data) and is equally
• comfortable working directly in the data tools to profile, query, validate, and review data. They set standards while
• working in close partnership with the teams that build and operate the pipelines and platforms.

• Key Responsibilities
• Enterprise Data Model & Architecture
• Semantic & Canonical Layers for Enterprise AI
• Integration Architecture (Boomi)
• Mergers & Acquisitions (M&A) Data Integration
• Platform Data Architecture
• Hands-On Data Analysis & Review
• Architecture Working Group & Decision Governance
• Cross-Functional Collaboration

• Required Qualifications
• ● 10+ years in data architecture, data modeling, enterprise data roles.
• ● Deep, hands-on experience architecting data in a highly customized Salesforce environment — custom objects,
• schema, and data model. (Must-have.)
• ● Demonstrated, hands-on experience with Snowflake and Boomi. (Must-have.)
• ● Deep, hands-on proficiency with the data tools used day-to-day for analysis and review — SQL, Salesforce
• (SFDC), Microsoft Fabric, and Snowflake. (Must-have.)
• ● Experience designing and enforcing a system-of-record model across a multi-system estate — defining
• canonical keys, cross-system identity spine design, and SoR governance. (Must-have.)
• ● Hands-on experience with NetSuite (ERP) data architecture.
• ● Experience with Zone Advanced Billing (ZAB) or comparable NetSuite-native subscription billing engines — ZAB
• subscription model, usage charge objects, and billing pipeline data design.
• ● Proven track record defining enterprise data models, canonical and semantic layers, and classification /
• taxonomy standards.
• ● Strong command of integration architecture and field-level data mapping across enterprise systems.
• ● Experience designing data constructs that support AI / ML and analytics use cases.
• ● Solid data governance, metadata, lineage, and data-quality fundamentals.
• ● Experience driving large-scale, evidence-based data quality remediation — measured profiling, root-cause
• analysis, remediation sequencing, and tracking outcomes to closure across a complex estate.
• ● Experience operating in or facilitating an architecture governance body — running design reviews, managing an
• open decisions register, writing decision records, and driving cross-functional alignment without direct
• authority.
• ● Proven experience converging a post-M&A or post-growth application estate onto a rationalized, canonical
• model — not greenfield architecture, but remediation and convergence in a complex, heavily-customized
• environment.
• ● Ability to set standards and influence across teams without direct authority; strong communication with both
• technical and business stakeholders.

Preferred Qualifications

• ● Experience enabling enterprise AI / GenAI initiatives (semantic layers, retrieval-ready / RAG data, feature
• stores).
• ● Experience with usage-based or consumption-based billing data models — including usage staging, aggregation
• pipelines, and multi-dimensional product calculation logic.
• ● Experience with identity resolution at scale — designing or operating matching algorithms, golden-record
• patterns, or SSO-to-CRM linking models across hundreds of thousands of accounts.
• ● Experience mapping and integrating data through mergers & acquisitions (M&A) or system-consolidation
• programs.
• ● Familiarity with data governance frameworks (e.g., DAMA-DMBOK) and data catalog / metadata tooling.
• ● Experience in a SaaS or technology-company environment.
• ● Relevant certifications (Salesforce, Snowflake, Boomi).
• ● Bachelor's degree in Computer Science, Information Systems, or a related field, or equivalent experience.