Accenture
Data Architect
$103K–$196K
Washington, DC +1 · Full-time · Posted Oct 6, 2026
- Location
- Washington, DC
Washington, District of Columbia, United States - Experience
- 8–12+ years in data engineering/architecture, with 3–5+ years architecting cloud data platforms (preferably GCP).
- Education
- Bachelor’s degree in Computer Science, Engineering, Data/Information Systems, or related field.
- Visa sponsorship
- Applicants must have U.S. work authorization that does not now or in the future require visa sponsorship. Must be a U.S. Citizen with ability to obtain a Public Trust clearance.
About the job
Architects and governs enterprise GCP data platforms, pipelines, and models, enabling secure analytics and AI/ML workloads for federal clients.
What you'll do
- Define GCP lake, lakehouse, warehouse, and streaming architectures, standards, and data models.
- Design and review secure, compliant data pipelines; optimize performance, reliability, and cost.
- Set architecture, IaC, CI/CD, and governance practices; maintain blueprints and mentor teams.
What they ask for
- U.S. citizenship and ability to obtain a Public Trust clearance; U.S. work authorization without current or future visa sponsorship.
- Bachelor’s degree in Computer Science, Engineering, Data/Information Systems, or a related field.
- 8–12+ years in data engineering/architecture, including 3–5+ years architecting cloud data platforms; enterprise data platform design experience.
- Hands-on expertise with BigQuery, GCS, Dataflow, Dataproc, Pub/Sub, and Cloud Composer; experience with security, governance, regulatory compliance, and Terraform/CI/CD.
Nice to have
- GCP professional certifications; federal government or regulated-industry experience.
- Vertex AI/MLOps, governance and metadata frameworks, or advanced BigQuery and GCS tuning experience.
Pay
$103,200 — $196,400 USD base salary
Tools
GCP, BigQuery, GCS, Dataproc, Dataflow, Pub/Sub, Cloud Composer, Terraform
AI focus
Enable Vertex AI pipelines, feature stores, and MLOps with reproducible, governed ML data pipelines.
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