Data Architect
HybridAtlanta, Georgia, United States
Job Summary
Define a managed AWS reference architecture delivering reliability without a large operations team. Specify a layered data model from raw to curated that excludes sensitive data, establishing governance across classification, PII handling, access control, lineage, and residency. Create reusable engineering patterns for capture, land-and-store, transform-and-serve, and govern to ensure consistent data product assembly. Design loose coupling from operational systems using change-data-capture or scheduled extracts. Set a two-speed guardrail making the governed, pattern-based path the default with narrow criteria for low-code workflows. Drop into delivery to build data products when the team needs extra hands. This senior role requires deep fluency in medallion architectures and managed AWS services like Glue and Lake Formation, with a focus on reducing GenAI token consumption. Hybrid schedule includes three days in our Atlanta, GA office.
Required Qualifications
- Senior data architecture experience with production AWS systems, including S3-based lake or lakehouse designs and a governed analytical layer
- Deep fluency with medallion or layered data architectures and the governance controls that ride across them
- Hands-on knowledge of managed AWS data services — Glue, Athena, Lake Formation, DMS or equivalent — with a strong bias toward managed over self-run
- Proven experience designing for data classification, PII handling, access control, lineage, and residency, ideally in a regulated or public sector context
- The judgment to build just enough: you can define a blueprint without over-engineering it, defer what the backlog doesn't yet need, and hand off clean, documented patterns a small team can execute against
- This position will be hybrid with 3 days/week in our Atlanta, GA office. (Tuesday, Wednesday and Thursday)
Desired Qualifications
- Experience designing contextual or semantic data layers that reduce GenAI token consumption so downstream AI features run faster and cost less
- Familiarity with dbt and warehouse-side modeling (e.g. Redshift) and with low-code orchestration such as n8n
- Experience with Canadian data residency requirements and multi-region AWS deployments
- A track record of standing up governance from day one rather than retrofitting it later
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