Data Architect

Tricascade Tech; United States; On-site; USD 140,000 - 200,000; Full time

Job summary

ConnectWise is seeking an experienced Data Architect to establish semantic and canonical data layers and reusable data constructs that underpin enterprise AI development. This hands-on architect will define the blueprints and standards while profiling, querying, and validating data in collaboration with pipelines and platforms.

The role requires deep Salesforce data modeling, Snowflake, Boomi expertise, and a proven track record delivering canonical models across a multi-system estate with

Qualifications

• Must-have hands-on data architecture experience with enterprise data models.
• Deep Salesforce data modeling experience including custom objects and schema.
• Proven proficiency with Snowflake and Boomi in complex estates.
• Strong data governance, metadata, lineage and data-quality fundamentals.
• Experience designing a system-of-record across multi-system environments.
• Familiarity with M&A data integration and canonical/semantic layers.

Responsibilities

• Establish semantic and canonical data layers for enterprise AI.
• M&A data integration and data construct design.
• Hands-on data analysis, profiling, and validation.
• Collaborate across data engineering, business applications, and integration teams.
• Set standards for architecture governance and cross-functional alignment.

Skills

Data architecture

Salesforce data model

Data governance

Data quality

Integration architecture

AI/ML data constructs

Canonical data models

M&A data integration

Stakeholder communication

Education

Bachelor's degree in Computer Science or Information Systems

Tools

Snowflake

Boomi

Salesforce

Microsoft Fabric

NetSuite

SQL

Job description

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

Semantic & Canonical Layers for Enterprise AI

Mergers & Acquisitions (M&A) Data Integration

Hands-On Data Analysis & Review

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.
• ● 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
• ● Ability to set standards and influence across teams without direct authority; strong communication with both technical and business stakeholders.

Preferred Qualifications

• ● Experience with Zone Advanced Billing (ZAB) or comparable NetSuite-native subscription billing engines — ZAB subscription model, usage charge objects, and billing pipeline data design.
• ● Experience enabling enterprise AI / GenAI initiatives (semantic layers, retrieval-ready / RAG data, feature pipelines, and multi-dimensional product calculation logic.)
• ● 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.