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.