Senior Data Architect

Jobtailor; Atlanta (GA); On-site; USD 140,000 - 190,000; Full time

Job summary

Jobtailor in Atlanta, GA seeks a senior Enterprise Data Architect to define and implement Canonical Models and Semantic Layers atop large data lakes. You will lead the design of an Enterprise Ontology, semantic APIs, and data contracts.

Collaborate with ML/DevOps to enable MLOps, FinOps awareness, and metadata standards, ensuring data is discoverable and machine-readable across the organization.

Qualifications

• Bachelor's degree in CS, IS, Data Analytics or IT.
• 5+ years in data engineering/architecture in enterprise context.
• Proven ability to design and scale Canonical Models and Semantic Layers on massive data lakes/lakehouses.
• Deep architectural knowledge of Snowflake, Databricks, or Microsoft Fabric and cloud ecosystems like AWS or Azure.
• Strong data modeling across relational, dimensional, and Data Vault 2.0 or graph concepts.

Responsibilities

• Architect the framework enabling data-driven decisions.
• Co-own the design of the Enterprise Context Layer.
• Define vision, requirements, and roadmap for the Ontology and Semantic Layer.
• Design and deploy semantic abstraction layers exposing data via APIs.
• Bridge big data performance with semantic meaning.
• Lead consolidation of data domains into Canonical Models.
• Implement lakehouse patterns.
• Partner with ML/DevOps to maintain MLOps processes.
• Develop enterprise metadata standards and data contracts.
• Ensure data and business logic are highly discoverable and machine-readable.
• Implement reusable data quality and identity resolution frameworks.

Skills

Canonical Models

Semantic Layers

Data Modeling

Cloud Data Platforms

FinOps

Data Lakes

MLOps Collaboration

Education

Bachelor's degree in CS/IS/Data Analytics/IT

Tools

Snowflake

Databricks

Microsoft Fabric

Job description

Responsibilities

• architecting the framework that empowers our entire organization to make high‑stakes, data‑driven decisions
• co‑own the design of the foundational AI Context Layer
• define the vision, requirements, and roadmap for an Enterprise Ontology and Semantic Layer
• design and deploy semantic abstraction layers to expose canonical data via intelligent APIs
• bridge the gap between physical big data performance and semantic meaning
• lead the design and consolidation of foundational data domains into unified, cleansed Canonical Models
• implement cutting‑edge, resilient lakehouse patterns
• partner with ML/DevOps teams to architect and maintain MLOps processes
• develop and enforce enterprise‑wide standards for metadata management, data contracts, and semantic version control
• ensure data and its underlying business logic are highly discoverable and machine‑readable
• implement reusable data quality and identity resolution frameworks

Requirements

• Bachelor’s degree in Computer Science, Information Systems, Data Analytics, Information Technology or similar major
• 5+ years of experience in data engineering and data architecture in a dedicated Enterprise or Domain Architect capacity
• Proven track record of designing, scaling, and implementing Canonical Models and Semantic Layers that sit on top of massive Enterprise Data Lakes/Lakehouses
• 5+ years of experience with modern cloud data platforms, specifically possessing deep architectural knowledge in at least one of the following: Snowflake (Dynamic Tables, Cortex, Horizon), Databricks (Unity Catalog, Delta Live Tables), or Microsoft Fabric (OneLake, Semantic Models), alongside cloud ecosystems like AWS or Azure
• Advanced skill in Data Modeling across multiple paradigms: Relational, Dimensional (Kimball), and highly relational/flexible frameworks like Data Vault 2.0 or Graph‑native concepts
• Demonstrated ability to build, maintain, and version‑control an ontology or semantic map (e.g., translating messy source attributes into a single, unified business entity layer)
• Solid understanding of FinOps — managing and optimizing cloud compute/storage consumption to maintain platform ROI while running complex semantic or AI workloads.