Top Remote Data Architect Jobs

Lead design and governance of enterprise-scale data architecture (warehouses, lakehouses, streaming). Define standards for data quality, lineage, observability, and AI-enabled workflows. Mentor engineers, serve as technical escalation, and translate business needs into long-term data architecture and governance strategies.

Lead the design and execution of a new enterprise data platform, ensuring metrics reliability and supporting AI-driven products, while mentoring engineers and collaborating across teams.

Lead enterprise AI transformation engagements as a senior strategic and technical advisor. Advise executives on AI strategy, design end-to-end AI and data architectures (RAG, knowledge graphs, MCP), architect data catalog and metadata strategies, embed AI governance and responsible AI controls, and drive adoption, change management, and practice development across customers.

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 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 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 systems and data architecture across business domains, define target-state architectures and integration patterns, rationalize shadow IT, guide sensitive-data placement in regulated multi-environment contexts, support major strategic programs, establish architecture governance and review practices, and coach engineering teams to raise architectural maturity.

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.

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.

Senior Data Architect contractor to accelerate and modernize the data platform: assess landscape, design end-to-end data solutions, define integration and metadata patterns, enable data mesh and cloud migration (AWS), and produce reusable architecture artifacts for handoff to engineering teams.

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

Lead design and implementation of scalable, secure data architectures (lakes, warehouses, pipelines). Provide technical leadership, mentor teams, enforce data governance and security (GDPR/HIPAA), optimize performance, review data models/ETL, and collaborate with stakeholders to deliver high-quality, maintainable data solutions.

Design and govern enterprise data architectures within the Informatica ecosystem. Lead data modeling, ETL/integration using Informatica tools, enforce data quality and governance, optimize performance, manage metadata and lineage, collaborate with stakeholders, document solutions, and train teams.

Lead architect to design and implement large-scale, distributed big data solutions using Java and Big Data technologies. Hands-on with Java 1.8+, Apache Spark, MapReduce, Hadoop/Cloudera, Hive, Impala, YARN, and Kafka. Perform data analysis, design scalable architectures, enforce testing (JUnit), and optionally use Unix/Python scripting. Manage global technology teams, apply industry best practices, and communicate effectively across stakeholders.

Lead design and implementation of scalable, secure data architectures (lakes, warehouses, pipelines). Provide technical leadership, mentor engineers, enforce data governance and security, optimize performance, review models and ETL code, and collaborate with stakeholders to deliver maintainable, compliant data solutions.

Design and implement scalable end-to-end data architectures, including data modeling, ETL/ELT pipelines, cloud data platforms, streaming integrations, governance, security, and enablement for analytics and AI/ML. Mentor engineers and document architecture for stakeholders.

Design scalable, secure data architectures on Google Cloud, lead discovery and migration from legacy systems, define ETL/ELT patterns, enforce governance and security, optimize performance, collaborate with stakeholders, and document architecture and migration progress.

Design and lead Snowflake-based data architectures and Informatica integration solutions. Build and optimize ELT/ETL pipelines (SnowPipe), data models (star, snowflake, Data Vault 2.0), ensure data security and governance, drive migrations to Snowflake, document architectures, and collaborate with engineers and analysts to meet SLAs.

Lead database design, data modeling, schema evolution, migrations, and ETL/ELT pipelines across MySQL, PostgreSQL, and Google Cloud databases. Build streaming and batch ingestion, enable CI/CD for data deployments, troubleshoot pipelines, produce runbooks, and mentor/lead offshore DB/ETL engineers while collaborating with onshore architects.

Lead design and implementation of scalable data architectures using Capsenta. Build and maintain data models, ontologies, and graph databases; manage databases; integrate data sources; optimize performance; enforce data governance; document solutions; collaborate with engineers and stakeholders; and stay current on semantic and knowledge-graph technologies.

Design, build, and optimize Spark ETL pipelines using Scala/Python and Oracle SQL. Lead and mentor a team of engineers, collaborate with stakeholders on scalable data solutions, ensure data integrity, security, and performance, and stay current on emerging technologies to drive improvements.

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.