Top Remote Data Architect Jobs

Design and develop cloud-based data platform solutions, including data pipelines, ingestion, transformation, cleansing, integrations, and data applications. Translate technical requirements into detailed designs, write reliable code, develop test automation, troubleshoot operational issues, tune batch and real-time processing, secure cloud data platforms, and implement CI/CD and monitoring. The role also involves advising client developers and defining efficient operational processes.

Designs and maintains scalable data architecture, Snowflake warehouses, ETL/ELT pipelines, dimensional data models, and governance processes. Partners with business stakeholders to deliver insights for pricing, inventory, customer segmentation, and marketing optimization. Builds reliable analytics datasets and dashboards, integrates data tools, monitors data quality, and ensures compliance within the regulated cannabis industry.

Designs and evolves enterprise data and AI platform architecture, enabling privacy-preserving cross-border data products, entity resolution, semantic standards, governed discovery, and AI-agent data access. Leads prototyping, reference implementations, technology adoption, and platform architecture decisions across engineering teams. Mentors engineers while applying expertise in distributed systems, cloud infrastructure, data modeling, governance, graph databases, and production operations.

Leads customer-facing cloud and AI data platform architecture on Microsoft Azure. Designs secure, scalable, resilient, and performance-optimized solutions; leads architecture sessions, proofs of concept, deployments, and modernization initiatives. Advises technical and business leaders, supports partners and sales teams, manages delivery risks, drives adoption and consumption, mentors colleagues, contributes to reusable frameworks and intellectual property, and influences product roadmaps through customer insights.

Lead the architecture and evolution of a Snowflake-based operational data platform. Design secure, governed, scalable data warehouse solutions, real-time ingestion, API integrations, AI-enabled capabilities, and natural-language querying interfaces. Define data flows, schemas, roadmaps, architectural standards, and governance while collaborating with engineering, data, business, and executive stakeholders. Troubleshoot complex platform issues, guide technical direction, and promote modern data engineering practices across enterprise systems.

Leads architecture and evolution of Snowflake-based operational data platforms, including real-time ingestion, AI-enabled capabilities, API integrations, data modeling, governance, and secure enterprise data flows. Partners with engineering, data, and business stakeholders to define roadmaps, standards, and technical direction while troubleshooting complex systems and communicating architecture decisions to technical and executive audiences.

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.

Serve as a trusted advisor and solution architect for enterprise Salesforce customers, specializing in Data 360. Lead discovery, requirements definition, architecture, system design, process documentation, risk management, stakeholder presentations, and complex workstreams. Guide customers in adopting emerging technologies and AI toolchains, resolve implementation roadblocks, manage expectations, and drive program strategies toward measurable business outcomes. The role requires extensive Salesforce and Data 360 expertise, strong consulting and communication skills, and up to 50% travel.

Design scalable human-data solutions for frontier AI clients, translating ambiguous model-training and evaluation needs into executable programs. Lead discovery, methodology, task and workflow design, feasibility estimates, expert profiling, quality strategies, and technical architecture in partnership with engineering and project teams. Advise on fine-tuning, RLHF, benchmarks, red teaming, multimodal data, coding tasks, and agent environments while guiding pilots through early delivery and developing reusable best practices.

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.

Leads enterprise architecture for data, analytics, and AI/ML platforms. Defines cloud, Lakehouse, streaming, governance, integration, and machine-learning architecture standards; guides modernization, proof of concepts, platform scalability, security, and cost optimization. Partners with executives, product owners, cybersecurity, governance, and engineering teams while leading design reviews, architecture forums, and technical programs. Requires deep experience with Databricks, cloud-native data platforms, distributed systems, data governance, and enterprise-scale architecture.

Lead enterprise Master Data Management strategy, architecture, governance, data quality, and integration initiatives across customer, product, supplier, employee, and financial domains. Design data models, hierarchies, matching and survivorship rules, integration patterns, and implementation roadmaps. Advise clients on Oracle and Salesforce ecosystems, lead workshops and executive presentations, guide solution delivery, mentor consultants, and contribute to proposals and statements of work.

Architects and standardizes cloud infrastructure for data platforms on GCP, including Kubernetes, networking, Terraform, GitOps, CI/CD, observability, performance, cost, security, and disaster recovery. Evaluates emerging data technologies, runs prototypes, guides managed-service connectivity, supports governance and consolidation, and enables engineering teams through architecture reviews, workshops, reference implementations, and documented standards.

Lead presales architecture and engineering for scalable data platforms using Microsoft Fabric and Azure. Responsibilities include client discovery, solution design, technical workshops, proposals, roadmaps, SOWs, demonstrations, and proof-of-concepts. Design data pipelines, warehouses, lakes, streaming architectures, and AI/ML infrastructure while advising on performance, governance, CI/CD, and infrastructure as code. Serve as a trusted technical advisor and Microsoft Fabric subject matter expert while collaborating with sales, governance, and AI architecture teams.

Leads enterprise data platform engineering and architecture across OCI, GCP, and Azure. Owns the modern data and AI operating system, metadata control plane, data catalog, security model, observability, and AI infrastructure including vector databases, knowledge graphs, feature stores, and RAG pipelines. Guides platform engineering standards, modernizes legacy ETL, establishes GitOps and Data-as-Code practices, and mentors global technical teams while presenting architecture to executive stakeholders.

Lead the strategy, architecture, and implementation of enterprise Azure data and AI solutions. Design scalable architectures using Microsoft Fabric, Synapse, Databricks, Azure databases, and AI services. Provide technical leadership, mentor engineering teams, oversee integrations, establish standards, and ensure security, governance, and operational excellence. Engage clients as a trusted technical advisor through workshops and executive presentations while partnering with project managers to deliver complex initiatives.

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.

Design, architect, and build batch, real-time, and event-driven data platforms and streaming applications. Integrate monitoring and IT operations tools, create data schemas and models, mentor peers, engage in pre-sales, and provide technical leadership and documentation for enterprise data solutions.

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.

Lead enterprise data and AI architecture for public-sector customers using Salesforce Data 360, Agentforce, and related platforms. Shape technical strategies, guide architectural discussions, validate security and feasibility, and build demos, prototypes, proofs of concept, and reference architectures. Partner with sales, product, engineering, support, and delivery teams to connect mission needs with scalable, governed, compliant AI solutions. Communicate complex technical concepts to executive and technical stakeholders and develop reusable enablement assets and 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 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.