Top Remote Data Architect Jobs

Design and implement scalable, secure enterprise data solutions on Databricks and Azure using Delta Lake and Medallion Architecture. Lead and mentor data engineering teams; define integration patterns, governance, security (Unity Catalog, RBAC, masking, row/column-level security), and CI/CD/IaC practices. Ensure data quality, lineage, monitoring, and optimize Spark/Delta workloads for performance and cost while aligning solutions with business needs.

Senior hands-on tech lead/solution architect for Banking & Capital Markets driving client relationships, solution design, proposals, and delivery of data modernization, streaming, and cloud-based data platforms. Leads cross-functional teams, mentors staff, supports revenue growth through upsell/cross-sell, and provides industry thought leadership and technical strategy.

The Data & Analytics Architect will design and implement analytics solutions, support client engagements, and lead data architecture projects, requiring extensive technical and consulting skills.

Lead full lifecycle implementations of Salesforce Data Cloud: design data models, integrations, segmentation, and activation. Act as primary technical expert for offshore teams, troubleshoot, build POCs, and enable personalized marketing using Salesforce platforms and data engineering best practices. Provide mentorship and stay current with Salesforce releases and AI/cloud trends.

Lead GTM technical engagements with data-platform ISVs to design architectures, build POCs, benchmarks, and enablement for NVIDIA acceleration across analytics, databases, and GenAI workflows. Create reference assets, demos, and training while partnering with product, engineering, sales, and customers.

Lead full Salesforce Data Cloud implementations: design data models, integrations, ETL, and segmentation; guide offshore teams; enable personalization with MCP/Einstein; run POCs and share knowledge while staying current on AI/cloud trends.

As an Enterprise Architect, you will manage architectural expertise, guide teams, analyze market trends, and develop architecture standards.

Design, validate, and deliver enterprise modern data management platforms (lakehouse, open table formats, object storage) with governance, compliance, streaming pipelines, metadata/catalog integration, federated query, and AI-ready data foundations. Build reference architectures, run POCs/labs, produce customer-facing guidance, and partner across product, engineering, and field teams to enable production-grade, compliant data solutions.

Design, build, and operate a centralized AWS data lake and AI experimentation platform. Define target-state architecture, guardrails, data contracts, and standards. Stay hands-on writing code, ship infrastructure, run reliability and cost controls, and hire and lead a small platform team while onboarding functional verticals and delivering production AI use cases.

Lead end-to-end architecture and delivery of production ML and generative AI platforms on Azure and Microsoft Fabric. Define MLOps, CI/CD, governance, observability, retrieval/LLM patterns, security, cost controls, and operational handoff. Work with data scientists and engineers to translate requirements, defend tradeoffs, and ensure systems run unattended in production.

As a Solution Architect, you will define and lead data platform deliveries, manage implementation teams, translate requirements into designs, and mentor team members.

Serve as the technical authority for the Enterprise Data Platform, defining enterprise data architecture, canonical data and semantic models, externalization and API principles, and AI/knowledge-graph ready designs. Lead solution architecture, govern semantic layers and Collibra integration, chair architecture reviews, shape technology roadmap, and partner with platform and trust teams to ensure consistent, governed data products across delivery teams.

Lead cross-discipline delivery and practice maturation across data engineering, visualization, governance, and AI. Orchestrate unified delivery approaches, set delivery standards and accelerators, coach architects, apply AI to improve delivery, and drive adoption of practice capabilities while managing stakeholder relationships and delivery risk on large consulting engagements.

Design and implement scalable batch and near-real-time data pipelines and storage on AWS. Define data architecture, ensure observability, optimize performance, lead production troubleshooting and migrations, enforce CI/CD and deployment best practices, and collaborate with stakeholders and platform teams to align solutions with business needs.

Design and implement scalable batch and near-real-time data pipelines and storage across AWS. Define event-driven integrations, ensure data quality and observability, optimize performance, lead production troubleshooting and migrations, review designs and CI/CD practices, and collaborate with architects and stakeholders to align solutions to business needs.

Customer-facing technical leader who architects, builds, and optimizes large-scale data engineering and lakehouse solutions on Databricks. Supports pre-sales and delivery with POCs, performance/load testing, workload sizing, migrations, observability, and adoption through workshops and community engagement.

Lead design and hands-on implementation of scalable data platforms on AWS and Snowflake. Build pipelines, storage layers, and data models; define ingestion, transformation, and quality standards; optimize performance and cost; ensure security and compliance; mentor engineers and partner cross-functionally to deliver production-ready, AI-ready data solutions.

Architect and deploy scalable Inventa data-management solutions, lead complex enterprise integrations (APIs, on-prem, cloud, SaaS, data lakes), resolve architectural performance and access issues, create global architecture guides and documentation, and feed product improvements through field insights. Customer-facing, cross-functional collaboration with Sales, Customer Success, and Product.

Senior AWS-focused cloud solution architect who defines and scales AI & Data delivery: builds reference architectures, presales S OWs/LOEs, provides technical SME support, and performs delivery oversight and architecture reviews to ensure repeatable, governed enterprise AI and data platform outcomes.

Lead architecture and evolution of enterprise-scale data, analytics, and MLOps platforms. Design AI-ready data foundations, semantic/ontology and federated catalog solutions, APIs and permission-aware discovery. Drive adoption through reference architectures, prototyping, R&D, and mentorship while ensuring security, governance, cost efficiency, and cloud-native operational excellence.

Serve as the technical bridge between GenLogs' data platform and customers: discover high-value use cases, communicate capabilities, build rapid prototypes/POCs (SQL, Snowflake, Python/Streamlit), translate requirements, and guide engineering/data teams to production while traveling to customers ~1-2 times/month.

Lead pre-sales data engineering engagements to design and implement scalable lakehouse data platforms (Snowflake/Databricks). Advise customers on data strategy, governance, pipelines, AI-ready foundations, migrations, and translate technical solutions into business outcomes while supporting sales and partner enablement.

Lead enterprise data architecture and governance across Microsoft Fabric, Azure, EDW and analytics. Define integration patterns, data modeling, lineage, security, DR/continuity and vendor standards. Guide engineering teams on implementation, performance tuning, cost optimization, testing, and responsible AI/GenAI integration. Ensure solutions meet regulatory, audit, and operational requirements while collaborating with business and IT stakeholders to translate needs into long-term platform roadmaps.

Design and advise on high-performance AI data infrastructure and storage solutions. Assess AI data readiness, map NVIDIA AI Data Platform integrations, guide data pipeline and lakehouse architectures, lead presales engagements, develop partner reference architectures, deliver workshops and enablement, and support field teams on enterprise AI workload outcomes.

The Associate Data/EDI Architect will manage implementation projects for employee benefits software, mentor teammates, and ensure quality execution while cultivating customer relationships.