Top Data Architect Jobs in NYC, NY

Lead design and implementation of the enterprise data platform: architect scalable warehouse/lakehouse solutions, build and optimize ETL/ELT pipelines, enforce data quality and governance, tune analytical workloads, and enable reporting and self-service analytics in support of BI and AI initiatives.

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.

Design, build, and prototype data platforms and streaming applications (Kafka, Spark, Flink). Create data schemas, integrate IT Ops tools (LogicMonitor, ServiceNow, BigPanda), configure platforms for performance/security, mentor peers, support pre-sales, and lead technical delivery across cloud environments.

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.

Design and implement enterprise data architectures and lakehouse/warehouse solutions using Microsoft Fabric, Databricks or similar platforms. Lead data modeling, ETL/ELT pipelines, cloud integration, CI/CD, and stakeholder-facing consulting engagements to deliver scalable, secure analytics systems.

Lead cloud data architecture and modeling for a federal court modernization program. Design and implement secure, scalable cloud data platforms (lake/lakehouse/warehouse), define data models, govern metadata and lineage, enable ETL/ELT and CDC ingestion, support migration and archival strategies, ensure compliance with federal security and data governance, and partner with engineering, governance, and BI teams to deliver analytics and AI/ML-ready data products.

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 and own end-to-end delivery of enterprise Data & AI programs, define data strategy and architecture (lakehouse/warehouse), drive modernization, governance, data quality, metadata/lineage, and AI adoption. Manage client relationships, account growth, program budgets, delivery teams, and stakeholder communications to ensure on-time, on-budget outcomes.

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.

Implement privacy-by-design and data risk management for DOHMH datasets: assess risks, apply mitigation (including differential privacy and synthetic data), operationalize confidentiality regulations, document methods, collaborate with stewards and engineers, and translate policy requirements into technical specifications and governance monitoring.

Design, build, and scale enterprise Databricks Lakehouse platforms. Lead architecture, platform standardization, ingestion frameworks (batch/stream), governance, performance/cost optimization, cloud integration, and mentor engineering teams.

Lead design and implementation of a medallion lakehouse on Microsoft Fabric, build ingestion pipelines, data models and BI dashboards, create AI/LLM tools for business users, enforce data governance, mentor data teams, and partner with stakeholders to enable self-serve analytics across marketing, product, finance, and clinical functions.

Senior hands-on Cloud Data Architect responsible for designing scalable, secure Snowflake-based data platforms and lakehouse solutions, enabling enterprise analytics and AI-native applications. Lead architecture, create design artifacts and blueprints, define scope and sizing, translate business requirements into technical solutions, collaborate with security and data teams, mentor junior staff, and guide implementation.

The role involves acting as a subject matter expert in Data and AI, providing technical expertise during sales processes for Azure-based solutions, and mentoring team members to enhance client experiences.

Lead enterprise analytics architecture and strategy across Epic Cogito, BI tools, and cloud platforms. Design scalable, secure solutions, enforce RBAC and DevOps/CI-CD practices, mentor federated teams, guide tool selection, and ensure alignment with business priorities. Provide architectural oversight, stakeholder consultation, and adoption planning for analytics initiatives in a large healthcare system.

Lead design, build, and support of scalable data pipelines and integrations using Microsoft Fabric, ADF, PySpark, SQL, ADLS Gen2, and Databricks Unity Catalog. Drive Azure-to-Fabric migration, stabilize pipelines, tune performance, manage data governance, troubleshoot issues, document designs, mentor team members, and collaborate with stakeholders in Life Sciences regulatory environments during US Eastern hours.

Design and deliver Databricks-centric data architectures, lead pre-sales and billable engagements, build end-to-end data engineering pipelines for AI/ML and BI, mentor teams, ensure data governance/security/quality, and resolve data system issues while producing solution documentation and presentations.

As a Salesforce Technical Architect focused on Data & AI, you'll design and implement solutions using Salesforce Data 360, oversee technical projects, collaborate with various stakeholders, and mentor junior staff to drive AI innovations.

Customer-facing specialist guiding enterprise cloud data engineering and lakehouse transformations. Architect and optimize large-scale data pipelines, perform performance and load testing, support pre-sales POCs and workload sizing, lead adoption workshops, and mentor peers to drive Databricks platform adoption.

Lead data architecture pursuits and complex client engagements, including workshops, requirements analysis, future-state architecture, implementation roadmaps, platform integration, and proof-of-concept development. Communicate complex solutions to technical and executive audiences, lead globally distributed teams, modernize legacy architectures, and provide thought leadership across data management, governance, modeling, cloud, and analytics technologies.

Lead enterprise data solution architecture by defining reference architectures, reusable patterns, and governance. Design scalable modern data platforms and pipelines, enable data product operating model, embed security and compliance, drive AI-enabled solutions, mentor architects, and align cross-functional stakeholders to improve reuse, data quality, and delivery speed across insurance domains.

Lead enterprise-level data solution architecture: define standards, reference architectures, and guardrails; design scalable modern data platforms and data products; embed governance, observability, and AI-enabled capabilities; influence stakeholders and mentor architects to drive adoption and reuse across insurance business functions.

Lead pre-sales technical engagements to design and optimize scalable cloud lakehouse data platforms (Snowflake/Databricks). Provide architecture reviews, ETL/ELT pipeline design, governance and AI-ready data foundations, support services sales, and translate technical tradeoffs into actionable recommendations for engineering and executive stakeholders.

Lead customer-facing data engineering and warehousing initiatives on the Databricks platform. Architect and optimize production-scale ETL/ELT pipelines, performance-test workloads, migrate legacy systems to cloud lakehouse architectures, support Solution Architects in technical sales, and provide training, demos, and community contributions.