Top Remote Data Architect Jobs

Lead enterprise data architecture across warehouses, data lakes, downstream applications, and AI workloads. Design data models, Medallion Architecture, ELT standards, semantic layers, APIs, access controls, and reusable datasets. Partner with business and BI teams to drive adoption, conduct architecture reviews, establish platform standards, and mentor data and analytics engineers. The role requires deep Snowflake, dbt, data modeling, pipeline, and semantic-layer expertise, with experience in AI data patterns and cloud infrastructure preferred.

Define and lead the architecture of NBCUniversal’s greenfield Microsoft Fabric enterprise data platform. Establish lakehouse, warehouse, integration, real-time streaming, data modeling, governance, security, DevOps, and observability standards. Translate architecture and business objectives into delivery roadmaps, epics, stories, and implementation plans while guiding multidisciplinary engineering teams. Design scalable solutions combining operational, historical, master, and reference data to support reporting, analytics, automation, AI, and reusable data products.

Leads enterprise data architecture and phased Microsoft Fabric implementation. Defines data models, integration patterns, governance standards, lineage, metadata, security, semantic layers, and scalable platform architecture. Partners with data engineering, IT, governance teams, business owners, analysts, and technology leaders to translate business requirements into sustainable technical solutions and support analytics, reporting, self-service, and AI enablement.

Leads the Enterprise Control Tower technical team and develops the enterprise data foundation supporting AI applications. Responsibilities include creating data products and ontologies, managing technical requirements and governance, overseeing engineering operations, mitigating technical risks, managing budgets and staffing, building stakeholder relationships, and hiring and developing architects and engineers. The role requires strategic leadership, enterprise data platform ownership, and delivery of measurable business value.

Lead the architecture and implementation of cloud-based lakehouse and data warehouse solutions. Translate client needs into technical designs, establish governance and data quality practices, automate cloud data platforms, and mentor data engineering teams. The role also supports consulting engagements, client presentations, deployment optimization, and adoption of Databricks, Spark, MLOps, and modern data engineering technologies across Azure, AWS, and GCP.

Designs and implements enterprise cloud data architectures, including pipelines, warehouses, lakes, migrations, schemas, security, governance, and analytics solutions. Collaborates with executives, stakeholders, architects, engineers, and security teams to deliver scalable, reliable, and compliant systems. Creates technical documentation, presents solutions, mentors technical staff, evaluates emerging technologies, and improves deployment efficiency. The role requires customer-facing consulting, architecture design, data engineering, cloud platform expertise, and hands-on experience with distributed data systems.

Designs, develops, and manages enterprise cloud data platforms using Snowflake, Python, and SQL. Builds automated ELT/ETL pipelines, medallion architectures, data warehouses, lakehouse solutions, and data models. Leads legacy-system migrations, data governance, metadata and lineage management through Alation, data quality frameworks, reporting datasets, and architectural documentation. Requires strong expertise in Snowflake, SQL, Python, data modeling, structured and semi-structured data, and modern cloud data practices.

Designs and implements enterprise Lakehouse, data warehouse, and ELT solutions using Snowflake, Python, and SQL. Builds Medallion Architecture pipelines, dimensional models, semantic layers, data marts, reporting systems, and migration frameworks. Administers Alation cataloging, lineage, metadata, governance, and data quality programs. Establishes architecture standards, documents best practices, monitors data processes, and mentors team members while leading complex cross-functional initiatives.

Lead technical delivery of Master Data Management solutions using Informatica MDM and PowerCenter. Design and optimize ETL workflows, mappings, data quality processes, governance practices, SQL data marts, and Python automation. Guide ETL specialists, troubleshoot production issues, support testing and performance tuning, and coordinate with state agencies, QA, development teams, and project leadership to deliver reliable cross-agency healthcare data integration.

Lead data cleansing, migration planning, mapping, validation, and cutover activities for a greenfield SAP S/4HANA implementation. The role identifies pre-migration work in ECC, manages migration objects and processes, troubleshoots complex SAP landscape issues, and collaborates with Digital Technology and business teams to deliver reliable data solutions. It requires strong SAP implementation experience, technical expertise, project leadership, business aptitude, communication skills, and U.S. citizenship.

Owns enterprise data architecture across on-premises and cloud systems. Designs data models, integration patterns, governance standards, security controls, and cloud migration strategies. Evaluates data platforms, documents architecture decisions, supports CUI compliance with NIST and CMMC requirements, and partners with technical, security, infrastructure, application, and business teams. Mentors engineers and analysts while communicating technical recommendations to executive and non-technical audiences.

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.

Leads the enterprise data architecture vision and multi-year roadmap centered on data mesh principles. Defines domain ownership, data products, platform architecture, governance, standards, interoperability, security, and quality frameworks. Partners with executives, engineering, security, privacy, and compliance teams to drive adoption and modernization. Chairs architecture reviews, evaluates technologies, guides proofs of concept, mentors architects and engineers, and builds business cases for platform investment and migration.

Own Snowflake architecture and establish staging, curated, and conformed data-layer standards. Design dimensional, historical, identity, payer attribution, member-month, and temporal models for healthcare data. Define data quality, reconciliation, lineage, audit, exception, and operational controls while protecting sensitive information. Translate requirements into engineering designs, guide engineers, conduct design reviews, manage technical risks, and support sprint planning and estimates.

Own the enterprise architecture, standards, governance, and shared platforms for AI and data across seven business units. Design scalable agentic AI, multi-tenant SaaS, Snowflake data architecture, security, privacy, observability, cost controls, and responsible AI practices. Build architecture standards into development workflows, evaluate vendors, guide legacy modernization, and advise executives. The role is hands-on, with 60–80% of time spent building, while mentoring architects and engineers.

Own clinical study data architecture from planning through database lock. Design EDC databases, specifications, edit checks, validation, and analysis-ready data structures; manage queries, data reviews, reconciliations, safety coding, change requests, reports, and audit-ready documentation. Collaborate with Clinical Operations, Biostatistics, Product, and program leadership while using Python, R, SQL, AI, and automation to improve data quality and delivery within GCP and regulatory requirements.

Owns data architecture and design authority for Plant to Stock ERP systems. Defines data models, governance, integration, transformation, reporting, analytics, security, and lifecycle practices. Approves functional and technical specifications, enforces integration standards, collaborates with functional and technical leads, and documents analytics architectures and metrics. Requires complex analytics experience, SAP analytics expertise, production or distribution domain knowledge, and the ability to communicate technical concepts to executives and nontechnical audiences.

Designs and manages enterprise data architectures, models, databases, ETL solutions, catalogs, metadata, and governance practices. Tracks legacy and 1LMx data through an enterprise modernization, ensuring data quality, lineage, retention, compliance, and fitness for reporting and analytics. Coordinates with federated governance teams, records managers, and diverse stakeholders to support transitional architectures and data standardization.

Leads secure, scalable customer data architecture across Adobe Experience Platform and cloud environments. Designs data strategies, models, governance frameworks, ingestion and integration solutions, migrations, and real-time customer profiles. Partners with data engineers, Adobe, and clients to address data quality, security, privacy, performance, and regulatory requirements. Uses SQL, scripting, APIs, and Postman to support implementation and automation while providing technical leadership across multiple customer projects.

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.

Own the architecture and standards for a trustworthy BI analytics platform. Design data models, ingestion and transformation patterns, lineage, PII controls, reliability SLAs, observability, schema governance, and cost management. Partner with engineers, analysts, business leaders, Security, Legal, and Compliance; enforce testing, CI/CD, infrastructure as code, and data quality practices. Mentor data professionals and document architectural decisions.

Leads enterprise data-platform architecture for clients using Microsoft Fabric and Azure. Responsibilities include discovery, target-state design, data modeling, migrations, DevOps and CI/CD, governance, security, AI/ML enablement, consulting, pre-sales, technical delivery leadership, mentoring, and development of reusable architecture assets. The role requires hands-on Fabric production experience, enterprise-scale implementation ownership, advanced SQL and Python/PySpark skills, client communication, and travel up to 25%.

Lead the architecture and implementation of scalable GCP and Databricks data lakehouse platforms. Design batch and real-time pipelines, data models, governance, cataloging, security, and performance strategies. Act as a technical lead and trusted client advisor while mentoring engineers, guiding architecture decisions, conducting proofs of concept, and supporting hands-on troubleshooting and delivery.

Designs and implements scalable data lakehouse platforms on GCP, including BigQuery, GCS, BigLake, and Dataplex. Leads real-time and batch data pipeline development, data governance, metadata management, security, and performance optimization. Partners with clients and stakeholders to translate business needs into architecture, leads technical teams, mentors engineers, and provides hands-on solutioning and technical advisory support.

Designs and optimizes enterprise data warehouse solutions, SQL queries, ETL workflows, and Tableau dashboards. Responsibilities include data ingestion, performance tuning, data quality validation, BI governance, documentation, and reporting automation using SQL, Python, and Tableau. The role collaborates with business partners to translate data needs into actionable insights and supports mission-critical analytics applications in a fully remote environment.