Data Architect

Location: Hybrid Remote in Atlanta (3 days onsite/week). Salary: Up to $220,000 (depending on experience) + bonus Short- and Long-Term Disability (STD/LTD) HSA & FSA options Paid Time Off (PTO) This Data Architect role owns the end-to-end design and evolution of an enterprise data platform, moving from the current state to a materially improved architecture that scales across domains. Success is defined by delivering a clear target-state data architecture, enabling consistent data sharing and reuse across systems, and putting governance in place so teams can trust and securely consume data. The role is hands-on and requires staying close to implementation while setting architectural direction. Responsibilities: Lead an enterprise data transformation from the current environment to a modern target-state architecture, clearly articulating what changes are required, why they improve outcomes, and how teams will execute them. Develop enterprise data models that define how data is structured, related, and shared across domains and systems, reducing duplication and preventing siloed definitions. Define and govern architectural standards and reference patterns for Azure-based data platforms, guiding implementation across services such as Databricks, ADLS, Delta Lake, Synapse, and/or Microsoft Fabric. Drive adoption of data governance practices including metadata management, lineage, data quality controls, cataloging, and enterprise data standards. Establish security and access-control patterns for data platforms, balancing least-privilege controls with reliable self-service access for approved users and systems. Partner with engineering teams to translate architecture into buildable epics and technical designs, reviewing implementations to ensure alignment with the target-state platform. Create clear architecture documentation (current state, future state, transition roadmaps, decision records) that enables consistent execution and simplifies onboarding for delivery teams. Guide data product and platform teams on scalable data consumption patterns (shared datasets, reusable definitions, and integration contracts) to support reporting and downstream applications. Required Skills: Demonstrated experience personally leading an enterprise data transformation from an existing environment to a materially better data architecture/platform, with the ability to explain what changed and the measurable benefits. Strong enterprise data modeling experience designing data structures, relationships, and shared consumption patterns across multiple systems, domains, or product modules. Architecture experience with modern Azure data platforms, including Databricks, ADLS, Delta Lake, Synapse, and/or Microsoft Fabric. Hands-on experience establishing enterprise data governance practices such as metadata, lineage, data quality, cataloging, security/access controls, and data standards. Senior-level, hands-on architecture leadership capability: able to set architectural direction while remaining close to implementation and delivery details. Preferred Skills: Production lakehouse experience with Databricks and Delta Lake, including Medallion/Bronze-Silver-Gold architecture patterns. Experience building shared enterprise semantic models, standardized KPIs, and reusable data definitions that work across business functions or product modules. Hands-on experience with Spark/PySpark, Python, SQL, and enterprise ETL/ELT or streaming data architectures. Experience designing data foundations that support AI/ML, RAG, or GenAI use cases, including scalable feature/data access patterns and governance considerations. #J-18808-Ljbffr