Top Remote Data Architect Jobs

The Data Architect/Data Governance Lead supports the Medicaid Enterprise Data Warehouse by leading data architecture, metadata management, and governance processes, ensuring compliance and scalability.

Responsible for designing and managing cloud architectures, migrating client systems to the cloud, optimizing data pipelines, and mentoring team members.

Lead design and governance of enterprise data architecture for an integrated care platform. Architect scalable Azure-based data platforms, data lakes/warehouses, ETL/ELT pipelines, and integration across EHR, Dynamics, claims, and third-party systems. Establish data governance, quality, metadata and MDM standards, ensure HIPAA/HITRUST compliance, leverage AI for system improvements, and partner with product, engineering, clinical, and business stakeholders to deliver secure, high-performing analytics and reporting solutions.

Analyze, validate, and transform healthcare payer data for HEDIS, CMS STAR Ratings, quality improvement, and regulatory reporting. Translate requirements into data solutions, source-to-target mappings, business rules, process flows, and functional specifications. Contribute to solution architecture, data modernization, governance, UAT, reconciliation, audits, and defect resolution. Collaborate with quality, population health, care management, technical, and client teams to resolve data issues and improve payer reporting and operational performance.

Designs and validates data solutions, database architectures, integrations, data models, pipelines, and process flows. Collaborates with analysts, engineers, architects, data scientists, and business stakeholders to solve complex problems. Develops analytic plans, produces data visualizations and executive reports, maintains data catalogs and quality standards, ensures privacy and regulatory compliance, and mentors teams on data maturity and process improvement.

Leads enterprise Data, AI, and digital transformation solution architecture and client pursuits. Designs scalable cloud, data, analytics, AI/ML, GenAI, and Agentic AI architectures; leads workshops, RFP responses, executive presentations, commercial closure, account expansion, and transition into delivery. Partners with engineering and delivery teams, mentors architects, and develops transformation roadmaps, business cases, accelerators, and industry thought leadership, particularly for Insurance and Financial Services clients.

Designs and architects data solutions involving relational and cloud databases, large-scale data processing, ETL, integrations, APIs, analytics, and reporting. Collaborates with technical and business teams to model scenarios, define requirements, validate deliverables, document data flows, maintain data quality and privacy standards, and communicate architecture recommendations. Provides data expertise, stakeholder engagement, coaching, and mentorship while developing scalable solutions for business processes and decisions.

Leads enterprise-scale AI, data, and cloud architecture initiatives for federal customers. Advises executives, designs Azure-based generative AI and agent solutions, modernizes document-intensive workflows, and governs secure, compliant, scalable architectures. Drives customer adoption, technical strategy, pre-sales opportunities, value realization, risk management, reusable intellectual property, and architectural community development. Mentors technical teams and ensures production solutions incorporate evaluation, observability, traceability, security, and human review controls.

Lead technical strategy for customer accounts, design scalable data engineering and real-time analytics architectures, and drive Databricks adoption. Advise senior customer stakeholders, lead architecture discussions, develop custom solutions for competitive opportunities, coordinate cross-functional teams, and influence product direction. The role requires deep expertise in Spark, Kafka, data warehousing, cloud platforms, Python, SQL, distributed systems, and production deployments. Travel may reach 30%.

Designs and positions enterprise backup and fast-recovery storage solutions centered on HPE Alletra X10000. Partners with customers, backup administrators, sales teams, and partners to assess environments, build capacity and performance sizing models, lead workshops and proofs of concept, validate recovery objectives, troubleshoot solutions, and support RFPs and competitive engagements. The role requires expertise in backup platforms, data reduction, enterprise file and object storage, ransomware-resilient architectures, and customer-facing technical presentations.

Leads customer-facing data platform and analytics architecture engagements for enterprise warehouse modernization. Designs scalable data lake and Lakehouse solutions, evaluates analytical workloads, sizes infrastructure, develops migration strategies, and advises on performance, governance, interoperability, and economics. Partners with sales, engineering, product management, and software vendors to create reference architectures, competitive strategies, and repeatable go-to-market motions involving Vertica, SingleStore, Cloudera, Splunk, Elastic, and HPE’s X10K platform.

Designs and delivers enterprise file and object storage architectures for unstructured data, hybrid cloud, AI inferencing, and RAG workloads. Leads customer workshops, assessments, proofs of concept, technical presentations, and pre-sales engagements. Advises on NFS, SMB, S3, performance, scalability, and cloud integration. Partners with product management to influence roadmaps, provides competitive analysis, and positions storage solutions for industry-specific requirements. Extensive customer and partner travel is required.

Advise enterprise clients on AI and data strategies, transformation roadmaps, operating models, governance, privacy, technology rationalization, and business cases. Lead discovery workshops, executive engagements, and art-of-the-possible sessions; prioritize use cases and connect technical recommendations to business outcomes. Build the advisory practice, develop offerings, manage multidisciplinary teams, mentor staff, strengthen client and partner relationships, and support successful distributed project delivery.

Own and architect the semantic layer and metrics/metadata for the data platform (Databricks/GCP). Build AI-ready models, enforce modeling and documentation standards, implement observability/testing for pipelines, enable self-serve analytics, and collaborate across product, clinical, and business teams to translate questions into reliable data solutions.

Design and optimize enterprise data architectures and pipelines using SQL, Spark/PySpark, Python, Apache Iceberg, AWS, ClickHouse, and PostgreSQL. Build greenfield application and data solutions, optimize databases and Spark jobs, integrate data virtualization and governance tools, and support CI/CD and infrastructure-as-code practices. Experience with financial services workloads is valued, while telecommunications knowledge is preferred but not required.

Lead data architecture consulting engagements, pursuit teams, client workshops, proofs of concept, and complex solution delivery. Design modern data architectures, integrate third-party platforms, create implementation roadmaps, and translate technical concepts for executive and technical audiences. Manage globally distributed teams, provide mentorship and thought leadership, support sales pursuits, and advise clients on data governance, quality, cataloging, lineage, master data management, cloud platforms, modernization, scalability, security, and AI-enabled solutions.

Support to evaluate and implement scalable data infrastructure. Work with technical teams to optimize data delivery and build reliable data systems. Expertise in data modeling, integration patterns, and data quality assurance is essential.

Design and own an enterprise-scale, multi-cloud data and analytics platform for the VA. Lead migration and modernization, implement governance/security/compliance for sensitive PII/PHI, enable AI/ML capabilities, support ingestion and interoperability across VA systems, and produce architecture and compliance documentation while collaborating with engineers, analysts, and stakeholders.

Own and implement the canonical data model and governance for a multi-tenant MEP SaaS platform. Architect data for AI/ML readiness (RAG, embeddings, vector search), design polyglot persistence and lake/lakehouse pipelines, lead staged modernization and migrations, produce hands-on prototypes and in-repo guardrails, and partner with platform, DB engineering, and ML teams to ensure data quality, lineage, and observability.

The Lead Data Architect will define enterprise data strategies, architect modern data platforms, lead pre-sales engagements, and ensure delivery excellence while mentoring team members.

Lead data architecture for a greenfield SAP S/4HANA implementation focused on data cleansing, mapping ECC to S/4, migration planning and execution, and validation during mock and go-live cutovers. Collaborate with cross-functional digital technology and business teams, troubleshoot complex SAP landscape issues, and recommend strategic improvements to ensure data reliability and accuracy.

Develop and implement a data management strategy, oversee data governance and architecture, ensure compliance, and manage vendor relationships to support organizational goals.

Define and govern enterprise data architecture, models, canonical and semantic layers, field-level mappings, and data governance. Partner with IT, Data Engineering, Security, and product teams to ensure data quality, lineage, integrations (Boomi), and platform alignment (Salesforce, Snowflake, NetSuite). Lead M&A data activities, perform hands-on data profiling and validation, and drive adoption of enterprise data standards to support analytics, AI, and automation initiatives.

Lead design and implementation of end-to-end ELT pipelines and transformation layers (dbt) to produce curated, reporting-ready datasets. Define data models, governance, metadata, lineage, and engineering standards. Partner with cross-functional teams to translate requirements, optimize performance and costs (cloud DW like Snowflake), and grow a data architecture practice that supports BI, self-service analytics, and AI agents.

Lead discovery workshops and architect Salesforce Data 360 solutions that unify enterprise data through ingestion, identity resolution, governance, zero-copy integrations, segmentation, and real-time activation. Design integrations across Salesforce clouds and external data sources, define marketing and customer lifecycle strategies, and support pre-sales engagements. The role requires hands-on Data Cloud implementation expertise, data modeling, privacy and consent knowledge, and active Salesforce certifications.