Top Remote Data Architect Jobs

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.

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, builds, and scales FourLeaf’s enterprise data platform. Responsibilities include data architecture, domain modeling, ingestion pipelines, Matillion ETL/ELT development, DataOps observability, Snowflake cost optimization, semantic-layer development, analytics enablement, and infrastructure supporting machine learning. The role leads large data initiatives, establishes engineering standards, ensures data quality and reliability, collaborates with business stakeholders and data scientists, and applies AI-assisted development practices.

Own the end-to-end architecture and roadmap for MyFitnessPal’s product data stack. Coordinate data engineering, business intelligence, product analytics, and backend teams; establish data movement and standardization practices; lead tool evaluations and platform migrations; implement governance, PII handling, deletion workflows, access controls, and cost optimization; and document architecture standards across the organization.

Leads the architecture and execution of migrating clinical, dental, pharmacy, and administrative data from more than ten legacy systems into MHS GENESIS. Responsibilities include source analysis, canonical data modeling, source-to-target mapping, ETL architecture, reconciliation, data-quality frameworks, cutover sequencing, tooling standards, team leadership, and production of migration artifacts for government review.

Lead a team of platform engineers while remaining hands-on in designing and implementing unified data platforms. Responsibilities include integrating siloed analytics applications, developing APIs and event streams, maintaining shared platform services, understanding distributed data pipelines, managing AWS infrastructure, applying infrastructure as code, and establishing deployment and reliability standards. The role also involves mentoring engineers, coordinating distributed contributors, evaluating cloud adoption, and translating technical decisions into business value, risk, and compliance outcomes.

Designs and advances enterprise data and AI architectures, including cloud platforms, data warehouses, lakehouses, machine learning, generative AI, integrations, and governance. Leads architecture standards, technical evaluations, proofs of concept, design reviews, troubleshooting, and implementation with engineering teams. Establishes data lineage, metadata, model governance, security, privacy, and compliance frameworks while advising executives on roadmaps, risks, trade-offs, and technology investments.

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.

Leads end-to-end architecture and delivery of Azure, Microsoft Fabric, and Databricks data and AI solutions. Responsibilities include discovery, solution design, presales, proposals, scoping, governance, CI/CD standards, client presentations, and production deployment. The Architect guides engineering teams, reviews deliverables, manages milestones, risks, budgets, and customer satisfaction, and translates business objectives into scalable lakehouse and data-platform architectures.

Defines and governs enterprise data and integration architecture across Microsoft Fabric, Azure, data lakes, warehouses, and business systems. Designs integration patterns, data models, governance, security, monitoring, continuity, and disaster recovery strategies. Guides engineering and vendor teams, translates business requirements into technical roadmaps, supports testing and quality standards, and integrates AI/ML and GenAI capabilities. Requires strong expertise in Microsoft data technologies, Power BI, DAX, SQL, Python, PySpark, enterprise integrations, and cloud ERP or CRM systems.

Leads data science strategy for a federal healthcare data platform. Designs data collection, validation, and analysis tools; develops predictive models; manipulates large datasets; and collaborates with scientists, trainees, and IT teams on cloud, interoperability, integration, security, and compliance solutions. Communicates technical recommendations to varied stakeholders and supports federal data security, ATO, and information management requirements.

Provides architecture guidance and technical leadership across AWS, SaaS, commercial applications, data platforms, and enterprise integrations. Assesses technical debt, security, product health, risks, and modernization opportunities; shapes technology roadmaps; establishes data ownership and authoritative sources; oversees data engineering teams and secure pipelines; and guides system, integration, and platform decisions. The role also mentors peers, collaborates with vendors, and supports procurement, issue resolution, governance, and enterprise technology planning.

Define and lead enterprise data-platform architecture across ingestion, storage, processing, governance, and consumption. Establish standards for data modeling and lifecycle management while partnering with engineering, analytics, machine learning, and business teams. Lead complex data-platform initiatives, implement governance and lineage capabilities, and guide scalable cloud architecture, security, networking, and cost optimization.

Leads the business architecture and transformation roadmap for compensation data, metrics, governance, and seller experiences. Partners with finance, engineering, product, operations, and field teams to define capabilities, requirements, processes, controls, and success measures. Drives cross-functional alignment, data quality improvements, business readiness, adoption, and executive decision-making while assessing impacts across compensation plans, reporting, tools, and operations.

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.

Performs structured data analysis under senior guidance to solve customer problems, identify patterns and anomalies, test hypotheses, and develop reusable data science components. Collaborates with engineering, mission operations, solution delivery, and customers to scope requirements, improve processes, and translate analytical findings into actionable business decisions. The role requires strong communication, coachability, analytical coding ability, and willingness to travel up to 50%.

Designs scalable, secure, resilient cloud and data architectures for high-volume services. Evaluates cloud technologies, develops reusable Terraform infrastructure and automation, and serves as a database architecture expert for PostgreSQL, Oracle, MongoDB, Redis, and Valkey. Builds prototypes and reference implementations, designs highly available distributed database systems, coaches engineers, partners with product and SRE teams, and converts validated concepts into production-ready architecture patterns.

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.

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.

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.

Define and improve hardware and software architectures for NVIDIA data processing platforms. The role focuses on hardware-software co-design, full-stack performance optimization, benchmarking, workload analysis, system trade-offs, and collaboration with customers, partners, architects, and engineering teams to guide scalable accelerated computing solutions.

Lead enterprise data and AI architecture across marketing, customer engagement, digital, sales, and analytics. Design scalable cloud data platforms, reusable data products, semantic models, real-time and batch architectures, governed AI capabilities, machine learning systems, generative AI, agents, recommendations, and personalization. Establish standards for governance, security, privacy, quality, lineage, and observability. Provide technical direction, lead architecture reviews and roadmaps, partner with engineering and data science teams, and mentor architects and engineers.

Leads ALSAC’s enterprise data privacy program, including privacy governance, risk and impact assessments, privacy-by-design, compliance metrics, consent, retention, data minimization, processing inventories, and privacy requests. Partners with Legal, Information Security, IT, Procurement, Data Governance, and business teams to implement controls, manage risks, support cloud and AI privacy requirements, deliver training, and monitor regulatory developments.

Lead enterprise data, ontology, cloud, and AI architecture across Palantir, Snowflake, and AWS. Define data models, governance, integration standards, platform roadmaps, and responsible AI patterns. Oversee Palantir Foundry and AIP ontology architecture, event-driven and API integrations, and AI/GenAI workflows. Lead architecture reviews, establish reusable standards, guide engineering teams, develop executive-level business cases, and align technology investments with business outcomes.

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.