Data Architect

Note: This is a Remote role with Occasional Travel (Central Region- 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 2 or more of our

served industries: Financial Services, Healthcare & Life Sciences, Retail & Consumer Goods,

Manufacturing & Supply Chain, Technology & Telco, Energy & Utilities, Media & Entertainment,

Government & Public Sector, Education, or Hospitality & Travel. Familiarity with at least one of

our core capability areas - Modern Supply Chain & Operations, Finance AI, Growth & Revenue

AI, Legal & HR Next, or Enterprise Office Transformation - is strongly preferred.

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