Top Remote Data Architect Jobs

Lead enterprise AI strategy and transformation engagements, advise executives, design end-to-end AI and data architectures (including RAG, knowledge graphs, data catalogs), define governance and responsible AI practices, drive adoption and change management, and develop reusable practice IP and thought leadership to enable scalable enterprise AI programs.

Lead enterprise AI transformation and solution architecture engagements from strategy through delivery. Advise executives, design end-to-end AI and data architectures (RAG, knowledge graphs, data catalogs), define governance and responsible AI frameworks, drive adoption and change management, and develop reusable practice IP and playbooks to scale AI across the ServiceNow platform.

Lead enterprise AI transformation engagements combining C-suite advisory, solution architecture, and change management. Design end-to-end AI architectures (RAG, knowledge graphs, Now Assist), data catalog strategies, governance, and adoption plans. Drive pilot delivery, reusable practice assets, and measurable value realization across complex, multi-stakeholder enterprise programs.

Lead enterprise AI transformation and architecture engagements from strategy through delivery. Advise executives on AI roadmaps, design end-to-end AI and data architectures (including knowledge graphs, data catalogs, RAG, and integrations), establish governance and responsible AI practices, drive adoption and change management, and develop reusable practice assets and thought leadership to realize business value.

Lead enterprise data architecture across multiple SaaS products by unifying reporting platforms, data models, and analytics capabilities. Assess current systems, define target-state architecture, establish data governance and quality standards, separate analytical workloads from transactional systems, and develop phased migration roadmaps. Guide database, engineering, and BI teams on cloud platforms, integration, modeling, performance, security, and reliability. Enable trusted cross-product reporting, governed self-service analytics, and data foundations for AI and advanced analytics.

Design and architect robust ETL/data pipelines on cloud platforms. Build and automate data ingestion and preprocessing using Spark/Databricks, AWS Glue, Airflow. Implement warehousing architectures (EDW, DM, ODS, MOLAP/ROLAP), ensure SQL-based data quality, use version control, and deliver tested production pipelines while communicating with stakeholders.

Lead design and implementation of data architecture and reliable ETL processes to move data between heterogeneous sources and targets. Troubleshoot and resolve data architecture issues, collaborate with business analysts and technology teams, set up and test systems, and optimize ETL performance to support domestic resilience initiatives.

Design, build, govern, and own an enterprise AI data platform that ingests, transforms, stores, and serves data for AI consumers. Define multi-domain data models, data contracts, pipelines, vector and retrieval infrastructure, observability for agentic behavior, and evaluation frameworks. Establish architecture standards, CI/CD, and infrastructure-as-code to enable production AI/ML and LLM applications.

Architects and scales cloud-native analytics platforms using Databricks and Snowflake. Builds automated pipelines, data models, decision engines, and AI enablement layers that integrate POS, syndicated, and internal data. Develops campaign measurement algorithms, productionizes analytical models, optimizes data warehouse ecosystems, and mentors data engineers. Translates business requirements into scalable SQL and Python solutions while communicating technical capabilities to business stakeholders.

Leads end-to-end Salesforce data migration and integration initiatives. Designs ETL processes, writes SQL and SOQL queries, develops automation scripts, performs data profiling and transformation, resolves migration issues, and ensures data quality, security, governance, reconciliation, and cutover readiness. Collaborates with Salesforce, integration, and business teams while documenting repeatable migration procedures and leveraging AI tools.

Serve as a senior advisor on enterprise data architecture and Adobe Experience Platform. Lead client discovery, design XDM schemas and identity resolution, guide data ingestion/ETL, governance, and Customer 360 initiatives. Provide technical leadership, mentor teams, review architecture, and contribute templates and best practices across consulting engagements.

Serve as a senior strategic and technical lead advising C-suite stakeholders on enterprise AI strategy, solution architecture, data catalog design, governance, and adoption. Design end-to-end AI architectures (Now Assist, AI Agents, RAG, knowledge graphs), lead pilot delivery, develop reusable practice assets, and drive AI governance, change management, and value realization.

Develop and maintain datasets for visualization and machine learning; automate data pipelines; partner with teams to build data products.

Lead enterprise data architecture for a multi-year SAP ECC to S/4HANA migration. Design canonical models, bridge reporting, integration patterns, and analytics enablement (SAC). Define standards, reference architectures, ETL/ELT pipelines, and governance; coach delivery teams and produce architecture artifacts aligned to TOGAF.

Design and operationalize FHIR-compliant data models and scalable integration solutions to harmonize EHR, HIE, and claims data. Build validation frameworks and automated rules to ensure clinical accuracy and longitudinal integrity. Produce clear documentation and collaborate with engineering and cross-functional teams to support analytics, operational, and research initiatives.

The Principal Data Engineer will lead data engineering efforts on public cloud, design scalable solutions, build data pipelines, and drive deliverables with a high level of technical expertise in relevant technologies.

Design and govern enterprise Salesforce data models, migrations, integrations, and governance. Ensure data quality, security, analytics readiness, and support Data Cloud, Customer 360, and AI use cases across complex ecosystems.

Design and lead cloud-native data architectures and end-to-end ELT/ETL pipelines across major cloud platforms. Build and optimize data lakes/warehouses, enforce data security and governance, implement IaC and CI/CD, conduct data profiling, and advise clients on AI/ML integration while mentoring delivery teams.

The Data Architect will integrate systems, collect and exploit datasets for operational needs, and ensure compliance in data handling. Responsibilities include cloud solution implementation, networking configuration, technical documentation, and project management.

Customer-facing Cloud Solution Architect driving security transformation on Azure and Microsoft 365. Design and implement security architectures (Identity, Threat Protection, Cloud Security), run design sessions, perform hands-on evaluations of Defender, Sentinel, and Azure AD, and influence product and engineering teams to improve customer security posture and adoption.

Lead the architecture and delivery of modern data and analytics platforms for clients. Design governed, secure solutions using Microsoft Fabric, Azure, Databricks, Power BI, and Purview. Translate business needs into scalable architectures, estimates, roadmaps, and delivery plans. Guide architecture reviews, governance, CI/CD, testing, monitoring, and operational readiness while enabling AI, Copilot, RAG, and intelligent application initiatives. Serve as the technical lead and trusted advisor for client engagements.

Own Marketing’s reporting and analytics layer by building executive dashboards, defining KPIs, modeling data across GTM systems, and establishing governance and trusted sources of truth. Partner cross-functionally to measure funnel performance, attribution, campaigns, pipeline, and ROI. Help evaluate and develop AI-powered analytics, conversational reporting, automated insights, and intelligent visualization while translating complex data into actionable recommendations for leadership.

Design, configure, and maintain Teamcenter BMIDE data models, translate Navy engineering and lifecycle requirements into PLM data structures, enforce data standards, produce documentation, support deployments, integrations, testing, and troubleshoot BMIDE/schema issues to enable a unified, scalable NPLM environment.

Design and lead end-to-end enterprise data and GenAI architectures, drive cloud migration/modernization, define GenAI/Copilot/agentic patterns (RAG, embeddings, vector search), establish MLOps/LLMOps and governance, ensure Responsible AI and security, and act as trusted technical advisor across presales through production.

Lead enterprise data architecture and transformation initiatives for financial-services clients. Responsibilities include defining target-state architectures, operating models, roadmaps, integration patterns, data governance, platform strategies, and architectural standards. The role evaluates vendors and build-versus-buy decisions, leads workshops and delivery teams, communicates with executives, manages complex projects, develops internal intellectual property, and mentors consultants. Strong expertise in MDM, data modeling, integration, cloud data platforms, governance, quality, security, and asset and wealth management data is required.