Top Remote Data Architect Jobs

Lead enterprise data architecture across warehouses, data lakes, downstream applications, and AI workloads. Design data models, Medallion Architecture, ELT standards, semantic layers, APIs, access controls, and reusable datasets. Partner with business and BI teams to drive adoption, conduct architecture reviews, establish platform standards, and mentor data and analytics engineers. The role requires deep Snowflake, dbt, data modeling, pipeline, and semantic-layer expertise, with experience in AI data patterns and cloud infrastructure preferred.

Designs and delivers Snowflake data architectures on AWS, including dbt-based data engineering and AI-enabled solutions. Leads RAG, vector search, embedding, semantic search, and analytics initiatives from proof of concept through production. Directs project teams, oversees solution quality and budgets, supports proposals and business cases, and serves as a trusted technical advisor to clients. Requires strong data engineering, governance, documentation, communication, and stakeholder-management skills, with travel as needed.

Lead complex data analyses, develop statistical models, write advanced SQL, build data models and dashboards, and establish technical standards for analytics. Mentor analysts, troubleshoot data quality and modeling challenges, partner with data engineering, translate ambiguous business questions into rigorous analyses, and communicate findings to senior stakeholders. Own the analytics function’s technical roadmap while ensuring data privacy and security practices.

Leads enterprise data warehouse, reporting, analytics, and transaction-processing architecture and modernization. Designs scalable on-premises and cloud solutions, modernizes ETL and SQL into Python automation, oversees BI delivery, and establishes DevOps and CI/CD practices. Provides hands-on technical leadership across development, testing, deployment, performance, security, and support. Leads proof-of-concepts, produces architecture documentation, presents recommendations, and mentors architects, engineers, developers, analysts, and testers.

Designs and leads scalable data architectures for enterprise applications built on Appian. Responsibilities include data modeling, relational database design, SQL optimization, integrations, data governance, security, performance troubleshooting, and technical reviews. Collaborates with architects, developers, federal stakeholders, and client leadership while mentoring technical teams and translating business requirements into secure, maintainable data solutions.

Designs and leads scalable, secure, and cost-efficient Snowflake data platforms supporting enterprise analytics, operational reporting, and generative AI applications. Serves as the technical authority for data architecture, modeling, lakehouse design, Snowflake services, dbt transformation frameworks, and Python/Snowpark development. Provides hands-on architectural leadership while influencing executive-level technology strategy.

Lead Salesforce Revenue Cloud data architecture and migration initiatives for CPQ and Billing implementations. Design data models, mappings, transformation logic, migration frameworks, and SQL-based extraction processes. Migrate revenue entities from ERP, billing, and legacy systems into Salesforce, validate data quality, and support testing and cutover. Facilitate customer workshops, manage stakeholders, and collaborate with architects, developers, RevOps, and QA teams.

Designs and leads enterprise cloud data platform architecture across ingestion, storage, processing, governance, and consumption. Establishes data modeling and lifecycle standards, guides platform strategy, and partners with engineering, analytics, machine learning, and business teams. Requires extensive data engineering and architecture experience, expertise with major cloud data platforms, production-scale streaming and processing technologies, data governance, cloud infrastructure, and leadership of complex cross-team initiatives.

Lead enterprise Microsoft Fabric data architecture, landing-zone design, governance, security, integration, semantic modeling, DevOps, and AI-ready platform delivery. Design scalable Lakehouse and Warehouse solutions, establish standards and operating models, guide Power BI and data engineering practices, automate deployments, and provide technical leadership across architecture reviews, discovery workshops, and implementation. The role requires deep Azure, Fabric, data engineering, security, and enterprise integration expertise.

Leads enterprise data architecture and engineering for a governed, cloud-based data platform. Designs data models, Snowflake ELT/ETL pipelines, medallion data layers, ingestion frameworks, and data quality controls. Establishes standards for metadata, lineage, governance, security, and reliability while optimizing performance and cost. Provides technical direction, mentors data engineering teams, evaluates emerging technologies, and partners with business, analytics, actuarial, and technology stakeholders.

Own university data integrations from source discovery through validated, signed-off feeds. Build SQL queries and scheduled extracts, model data, support partner upgrades and migrations, translate institutional policies into accurate data feeds, and improve monitoring, documentation, and reusable integration patterns. Collaborate with registrars and database administrators while supporting a named set of university partners. The role requires deep experience with student information systems, including PeopleSoft, and occasional travel for partner onsite engagements.

Designs and implements the data architecture supporting engineering technology, analytics, automation, and AI. Assesses current systems, defines target architecture and governance, develops data models and ETL/ELT pipelines, integrates engineering platforms, and establishes metadata, lineage, stewardship, access, and quality standards. Partners with engineering and Digital Engineering teams to deliver reusable data assets, dashboards, and analytics solutions while coordinating data protection, platform evaluations, roadmaps, and stakeholder communication.

Lead customer-facing architecture for AI data platforms and AI Factory environments. Design data-centric solutions for RAG, inference, and training workflows; size GPU and storage environments; optimize data movement, retrieval, latency, throughput, cost, and reliability. Partner with customers, sales, and Product Management to qualify opportunities, influence product roadmaps, create reference architectures, and develop scalable go-to-market solutions.

Designs and delivers Microsoft Fabric, Azure AI, Power BI, and generative AI architectures for enterprise clients. Leads solution design, prototyping, implementation readiness, governance, quality assurance, and client enablement across complex engagements. Develops AI solution patterns including RAG, vector search, embeddings, semantic search, and prompt orchestration. Leads project and client teams, supports business cases and proposals, reviews technical deliverables, manages risks, and serves as a trusted technical advisor.

Design and govern end-to-end data architecture for an integrated supply-chain e-commerce platform: create data models, build scalable ETL/ELT pipelines, ensure GDPR-compliant data governance, enable real-time analytics, optimize databases, plan retention/archival, and prepare data for LLM fine-tuning and RAG use cases.

Design and maintain scalable HR data architecture in Snowflake; build and optimize ETL/ELT pipelines with Matillion; enforce data governance, quality, lineage and security; manage SQL Server metadata environments; implement DevOps for data assets; partner with stakeholders and support AI-ready semantics and reusable data products.

Design and optimize Oracle CX data architectures, models, integrations, governance, and conversion processes. Lead large-scale ETL and migration initiatives from legacy systems, resolve complex data issues, establish quality frameworks, and collaborate with business and technical stakeholders. Provide technical leadership, conduct workshops, support project teams, and identify process improvements across Oracle CX, ERP, HCM, and third-party platforms.

Designs and governs enterprise data architecture across Oracle ERP, SCM, CX, and related applications. Leads data modeling, large-scale migration and conversion, integration architecture, data governance, quality management, and validation initiatives. Partners with business and technical stakeholders to define scalable solutions, leads architecture workstreams, mentors project teams, and supports Oracle Cloud implementations and digital transformation programs.

Lead and own end-to-end delivery of enterprise Data & AI programs, define data strategy and architecture (lakehouse/warehouse), drive modernization, governance, data quality, metadata/lineage, and AI adoption. Manage client relationships, account growth, program budgets, delivery teams, and stakeholder communications to ensure on-time, on-budget outcomes.

Design and own an event-driven data architecture that moves healthcare claims data through AWS and Snowflake into fraud, waste, and abuse alerts. Establish architecture standards, approve material changes, build complex pipeline components, and ensure scalability, reliability, and compliance with PII/PHI constraints. Collaborate with data science, compliance, technical, and investigative teams while supporting government review timelines. This is a hands-on principal role requiring strong Python, SQL, AWS, Snowflake, and production streaming pipeline experience.

Designs and supports scalable cloud data warehouses for CMS healthcare fraud, waste, and abuse analytics. Responsibilities include data modeling, healthcare interoperability, secure HIPAA-compliant governance, lineage, testing, CI/CD, automation, workflow scheduling, and technical architecture. The role integrates claims and healthcare domains using Snowflake and industry standards while collaborating with stakeholders, documenting solutions, and leading warehouse project delivery.

Designs and implements scalable data architectures, ingestion and transformation pipelines, API integrations, cloud data solutions, and data governance practices. The role supports analytics, business intelligence, dashboards, and AI models while optimizing infrastructure performance and cost. Responsibilities include data modeling, security, quality, lineage, compliance, documentation, and collaboration with cross-functional stakeholders. Requires expertise in Microsoft Fabric, AWS and Azure data services, SQL, Python, Tableau, and modern ETL/ELT practices.

Lead client-facing architecture for Microsoft Data & AI solutions, translating business priorities into secure, governed, scalable architectures and modernization roadmaps. Design lakehouse, batch and streaming platforms using Fabric, Databricks, Azure, Power BI, and related governance tools. Architect AI-ready data platforms supporting generative AI, agentic AI, RAG, vector search, and enterprise data agents. Support presales, proposals, estimation, executive presentations, implementation guidance, and mentorship of architects and engineering teams.

Leads corporate data architecture, standards, and data modeling for database and business intelligence projects. Designs logical and physical data models, source-to-target mappings, data warehouses, and integration architectures. Manages master and reference data initiatives, metadata repositories, data dictionaries, governance policies, data quality rules, and golden records. Provides technical leadership, mentoring, documentation, project guidance, and support throughout the systems development lifecycle.

Lead enterprise data architecture across AWS and Databricks Lakehouse: design scalable data models, ensure governance and data quality, mentor teams, evaluate and adopt data technologies (Delta Lake, Unity Catalog), oversee large projects and deliverables, and incorporate generative AI to accelerate data modeling and delivery.