Technical Architect – Enterprise Data

Arista Networks

. Define enterprise data architecture across Fabric, Data Lake, EDW, and analytics platforms .

Posted 10/21/2026full-timeRemote • Texas • United StatesSeniorLeadWebsite

Core Competencies

Role fit

Core Competencies

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Expertise in enterprise data architecture, integration patterns, and data governance, with a strong focus on Microsoft technologies and AI/ML integration. Proven ability to translate business requirements into technical specifications while ensuring compliance with security and regulatory standards.

Highest-signal resume keywords

Enterprise Solution ArchitectureMicrosoft FabricData LakePower BIETL/ELT Pipeline Design

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

DAXPower QuerySQLPythonPySparkData ModelingMetadata ManagementData GovernanceAI/ML IntegrationAutomation

Soft Skills

CommunicationStakeholder ManagementProblem-Solving

Tools & Technologies

Azure Data LakeData WarehouseJiraGitCI/CDSaaSCloud ERPCloud CRM

Industry Keywords

Enterprise Data ArchitectureData IntegrationData QualityRegulatory ComplianceOperational Excellence

Tech Stack

Tools & technologies

AzureCloudERPETLPySparkPythonSDLCSQL

About the role

Key responsibilities & impact

Define enterprise data architecture across Fabric, Data Lake, EDW, and analytics platforms
Design integration patterns for ingestion, transformation, and consumption
Create architectural flows and reference models
Establish standards for data modeling, metadata, lineage, and governance
Implement data validation, logging, monitoring, lineage, and RBAC
Ensure compliance with enterprise security, confidentiality, and regulatory standards
Drive platform cost optimization, performance tuning, and operational excellence
Enforce architectural governance and adherence to standards
Collaborate with business stakeholders and source system teams to understand data requirements
Translate business needs into technical specifications and architectural roadmaps
Review user stories and provide architectural guidance to development teams
Support QA and functional teams in defining testing strategies
Ensure delivered solutions align with business needs and architectural intent
Integrate AI/ML models and GenAI capabilities into data products and workflows
Evaluate emerging technologies and recommend adoption strategies
Guide teams on responsible AI usage and integration patterns
Conduct root cause analysis for data issues and identify improvement opportunities
Manage platform reliability, data quality, and governance processes
Define continuity strategy for data and integration platforms
Identify architectural risks such as single points of failure, dependency bottlenecks, and data corruption risks
Design disaster recovery and continuity across ERP, CRM, Data Lake, Fabric, and analytics systems
Ensure teams can execute continuity plans and that plans meet audit and security requirements
Set vendor expectations for process adherence, development methodology, documentation, and delivery timelines
Establish quality gates, review cycles, and acceptance criteria for vendor deliverables
Conduct vendor checkpoints, monitor progress, identify risks, and ensure architectural alignment
Provide technical guidance to vendor engineers on scalable, secure, and compliant solutions
Report to the IT Applications team and work with key IT stakeholders

Requirements

What you’ll need

10+ years in enterprise solution architecture, data engineering, and software development
Degree preferably in Computer Science, Information Technology, Management Information Systems, or Accounting
Proven experience designing end-to-end integrations, data platforms, and automation for large enterprise environments
Strong hands-on expertise with Microsoft Fabric, Data Lake, Data Warehouse, Data Pipelines, and the broader Microsoft ecosystem
Deep experience with Power BI semantic models, datasets, dashboards, and reporting
Advanced proficiency in DAX, Power Query, SQL, Python, and PySpark
Demonstrated experience architecting ETL/ELT pipelines integrating diverse data sources into Azure Data Lake and EDW
Strong understanding of data modeling, normalization, metadata management, and enterprise data security
Exposure to AI/ML, Copilot, GenAI, LLMs, prompt engineering, and AI API integration
Familiarity with SDLC, software quality practices, Jira, Git, and CI/CD
Experience with SaaS/Cloud ERP or CRM systems such as NetSuite, Salesforce, or SAP S/4HANA
Excellent communication, stakeholder management, and problem-solving skills

Benefits

Comp & perks

Remote work; role can be located anywhere in the United States
Equal opportunity employment
Confidential handling of applicant information according to EEO guidelines