Top Remote Data Architect Jobs

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.

Leads technical delivery of Master Data Management solutions using Informatica MDM and PowerCenter. Designs and implements ETL mappings, workflows, transformations, data quality processes, governance practices, SQL data marts, and Python automation. Oversees MDM specialists, monitors production jobs, troubleshoots operational issues, supports testing and validation, tunes performance, documents technical solutions, and collaborates with state agencies, QA, business teams, and project leadership.

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.

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.

Lead the architecture and implementation of enterprise-scale GCP data ecosystems, including PB-scale platforms and AWS-to-GCP migrations. Establish data platform roadmaps, self-service architectures, governance, security, quality, and Infrastructure as Code standards. Architect solutions using GCP data, analytics, AI, streaming, and containerization technologies. Lead cross-functional engineering teams, mentor staff, advise executives, manage technical risks, and communicate the business value of data initiatives.

Lead the design, structuring, and governance of Humana's cyber threat intelligence. Own Anomali ThreatStream administration, integrations, data quality, and collection management. Build pipelines and APIs to make CTI usable by analysts and AI/automation, and partner with stakeholder teams to optimize CTI for detection, SOC, and vulnerability workflows.

Own end-to-end data platform architecture across ingestion, lakehouse, warehouse, transformation, modeling, governance, and analytics delivery. Build pipelines, Spark and SQL transformations, data models, and production code. Design Databricks or Microsoft Fabric lakehouses, implement Delta Lake and medallion architecture, establish access controls and governance, and integrate databases, SaaS applications, APIs, files, and legacy systems. Evaluate platform choices based on client workloads, licensing, skills, and cost.

Lead complex enterprise data security deployments and serve as the technical authority for the Data Security portfolio. Develop reference architectures, playbooks, templates, runbooks, and field methodologies; enable and mentor delivery teams; maintain a validation lab; and convert escalations into reusable assets. Own new product introduction for data protection releases, partnering with Product teams before and after general availability. The role requires deep expertise in enterprise security, data protection, integrations, and regulatory standards.

Lead enterprise data architecture for Privia Health’s Snowflake platform, defining scalable modeling, integration, governance, security, and optimization standards. Design Medallion Architecture layers and healthcare data schemas spanning EMRs, claims, eligibility, and value-based care data. Establish dbt, Python, testing, orchestration, and CI/CD best practices; enforce HIPAA, PHI/PII masking, access controls, lineage, and cataloging. Provide technical leadership, design reviews, mentorship, and cross-functional guidance to engineering, analytics, clinical, and product stakeholders.

Leads healthcare data architecture, modeling, normalization, transformation, and integration across FHIR, OMOP, STDM, HL7, and related standards. Oversees data pipelines, terminology mapping, deduplication, quality initiatives, interoperability strategies, and technical documentation. Collaborates across technical and non-technical teams to resolve complex data issues and explore AI and machine learning applications. Requires deep expertise in clinical informatics, healthcare data standards, SQL, Python, R, dbt, ETL, cloud platforms, and version control.

Lead financial reporting delivery and data pipeline operations while improving data controls, quality, lineage, audit readiness, and regulatory compliance. Automate manual workflows using Alteryx, Python, and SAS; resolve production issues; partner with Technology on data models, testing, and enhancements; and analyze datasets for stakeholder reporting. Contribute to metadata, data dictionaries, responsible AI, and scalable data modernization initiatives.

Design and govern an enterprise cloud data platform and integration pipelines (primarily Snowflake). Define data models, medallion layers, and standards; build ELT/ETL pipelines, CDC/event-driven ingestion, data quality, metadata, and lineage. Partner with business stakeholders, mentor engineers, and provide architectural oversight to support analytics, reporting, and operational use cases.

Lead the architecture and implementation of complex cloud-based data solutions for customers. Define strategic data roadmaps, support pre-sales engagements as a data engineering subject matter expert, interview and mentor architects and engineers, and oversee data standards and operating procedures. The role requires extensive AWS data architecture experience across traditional and modern data platforms, including big data, machine learning, generative AI, DataOps, infrastructure as code, CI/CD, and Python automation.

Designs and leads modern, scalable data platforms using Snowflake, dbt, and AWS. Responsibilities include data modeling, batch and streaming pipelines, governance, security, privacy, migration from legacy systems, deployment automation, observability, testing, and enterprise reporting. The role collaborates with technical and business stakeholders, establishes architectural standards, mentors data engineers, and guides platform modernization while balancing performance, maintainability, scalability, and cost.

Defines enterprise data architecture strategy while building scalable ELT/ETL pipelines, governed data products, analytics-ready models, and cloud data platforms. Leads BigQuery optimization, orchestration, data quality, observability, CI/CD, infrastructure-as-code, modernization, governance, privacy, security, and integration standards. Partners with executives and cross-functional teams to establish architecture direction, data contracts, domain models, and multi-year roadmaps while mentoring senior technical staff.

Leads the architecture, design, and implementation of scalable GCP and Databricks data lakehouse platforms. Designs real-time and batch pipelines, data models, governance, cataloging, security, and performance optimization. Advises clients, translates business requirements into technical solutions, leads project teams, mentors engineers, reviews architectures, and balances strategic planning with hands-on proof-of-concept and troubleshooting work.

Assess legacy on-premises infrastructure and design a cloud-native data architecture for AccuWeather For Business. Create current- and target-state designs, modernization roadmaps, sequencing plans, technical specifications, and risk mitigations. Partner with engineering and data teams to implement scalable, secure, resilient backend data systems while maintaining reliable enterprise data delivery. Contribute hands-on code, data models, schemas, capacity estimates, cost analysis, and architecture decisions.

Define and govern enterprise data architecture, integration frameworks, data models, governance standards, and scalable GCP data platforms. Lead architecture decisions covering batch and real-time processing, Data Mesh and Lakehouse patterns, ETL/ELT, APIs, streaming, security, performance, observability, privacy, and compliance. Partner with technical and business stakeholders, guide data initiatives, establish platform standards, and mentor engineering teams on architecture and integration best practices.

Support and architect clients' Azure data platforms and Power BI environments within Managed Services. Design Databricks Lakehouse and Delta Lake solutions, build and maintain data pipelines, advise on governance/licensing, resolve escalations, mentor junior staff, communicate with clients, create documentation, and promote best practices for HIPAA-compliant healthcare data solutions.

As a Data Architect, you'll design, implement, and maintain data infrastructure, and lead the delivery of new data solutions in a collaborative environment.

The Data Architect will design business data models, define data architecture frameworks, mentor teams, and enhance data governance across AI and data initiatives.

The Data Architect will design scalable data models, transform raw data into actionable insights, and deploy analytics solutions for healthcare providers, with a strong emphasis on SQL proficiency and cloud technologies.

Lead the architecture and implementation of enterprise-scale Azure data and AI platforms, including data lakes, lakehouses, warehouses, integrations, machine learning, and generative AI solutions. Establish governance, security, MLOps, and AI frameworks; guide cloud modernization, migration, performance, and cost optimization. Translate business needs into technical architectures, present recommendations to executives, lead architecture reviews, support client pursuits, and mentor engineering teams.

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.

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.