Data Architect

BrainWave Professionals; United States; Remote; USD 120,000 - 190,000; Full time

Job summary

BrainWave Professionals is seeking a hands-on Data Architect to lead enterprise data architecture engagements for clients across various industries. The role focuses on scalable, governed data architectures, data modeling, platform strategy, and federated data mesh design, working closely with engineering teams to translate designs into production-grade solutions.

You will drive data quality, lineage, MDM, and governance, while shaping data architecture standards and reference architectures for

Qualifications

• Must have hands-on expertise in data modeling across conceptual, logical, and physical layers.
• Strong SQL skills with optimization experience for large data sets.
• Experience with data warehousing and lakehouse patterns in cloud environments.
• Proven data governance frameworks and metadata management knowledge.
• Hands-on experience with cloud data platforms (AWS/Azure/GCP).
• Familiarity with REST and event-driven integration patterns.

Responsibilities

• Design data models aligned to client domains and requirements.
• Define enterprise data architecture standards, governance, and federation patterns.
• Develop data lineage, MDM, and metadata management frameworks.
• Translate regulatory and operational data needs into architecture choices (HIPAA, PCI-DSS, etc.).
• Align architecture with client priorities like Finance AI and Supply Chain modernization.
• Collaborate with engineering to validate designs against implementation realities.
• Produce ADRs and reference architectures for clients.
• Drive data quality, observability, and SLA frameworks as architectural concerns.

Skills

Data modeling

SQL & query optimization

Data warehousing / lakehouse

Data governance

Cloud data platform architecture

REST & event-driven integration

Job description

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 and federated governance patterns 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,
• 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
• 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