Data Architect

Note: This is a remote position with occasional travel required across the East Coast and Central regions of the United States. Job Title-Data Architect Job Description We are seeking a hands-on Data Architect with strong engineering sensibilities to lead enterprise data architecture engagements at client sites. In this client-facing role, you will own the design and delivery of scalable, governed, and future-ready data architectures – spanning data modeling, platform strategy, and federated data mesh design - while working closely with engineering teams to ensure architecture translates into working, production-grade solutions. You will serve clients across Financial Services, Healthcare, Retail, Manufacturing, Technology, Energy, Media, Government, Education, and Hospitality sectors, and must bring the adaptability to translate industry-specific data requirements into robust architectural solutions. Key Responsibilities ● Design conceptual, logical, and physical data models aligned to client business domains and operational requirements ● Define and enforce enterprise data architecture standards, patterns, and governance frameworks across client environments ● Lead data mesh design including domain ownership models, data product definitions, and federated governance patterns ● Architect data platform strategies covering ingestion, storage, transformation, serving, and consumption layers ● Develop data lineage, master data management (MDM), and metadata management frameworks ● Translate industry-specific regulatory, compliance, and operational data requirements into architecture decisions (e.g., HIPAA for healthcare, PCI-DSS for financial services, CMMC for defense) ● Align data architecture to client capability priorities including Finance AI, Growth & Revenue AI, Supply Chain modernization, and Enterprise Office Transformation ● Collaborate with engineering teams to validate architecture blueprints against implementation realities and adjust designs accordingly ● Produce client-facing architecture decision records (ADRs), reference architectures, and data strategy roadmaps ● Drive data quality, observability, and SLA frameworks as first-class architectural concerns Soft Skills & Culture Fit Client presence, ownership mindset, clear communicator, collaborative, intellectually curious, delivery-oriented, industry-adaptable Industry & Domain Exposure Candidates should have working experience or demonstrable exposure across industries like Financial Services, Insurance, Healthcare, Technology & Telco. Technical Requirements Must-Have Skills ● Tier 1: Data modeling (conceptual/logical/physical), SQL and query optimization, data warehousing and lakehouse patterns, data governance frameworks, cloud data platform architecture (AWS/Azure/GCP), REST and event-driven integration patterns ● Tier 2: Data mesh and data product design, metadata management and data catalogs, streaming and batch ingestion architecture, column-level lineage tooling, schema registry and schema evolution patterns Nice-to-Have Skills Exposure to graph data models or knowledge graph concepts, semantic layer design, MLOps data contracts, federated query architecture, policy-as-code for data governance Logistics