Data Architect

Role overview Set the architecture and technical standards for enterprise data platforms on Google Cloud, spanning data lakes, warehouses, streaming pipelines, analytics, and AI/ML use. This senior role combines hands-on design with governance, security, performance, cost management, documentation, and cross-functional technical leadership.

Responsibilities - Define target architectures and data zones, along with standards for ingestion, transformation, consumption, schema evolution, and retention. - Design data models and scalable batch, streaming, and event-driven pipelines using the cloud platform’s analytics and processing services. - Establish security and governance controls, including least-privilege access, encryption, private networking, metadata, lineage, and data quality. - Enable governed machine learning workflows with reproducible data pipelines, provenance, feature stores, and operational practices. - Improve query and storage performance, cost, monitoring, logging, and operational metrics. - Maintain architecture blueprints and reference implementations; review models, pipelines, infrastructure code, and security designs; mentor teams and document decisions.

Requirements - U.S. citizenship and ability to obtain a Public Trust clearance. - Bachelor’s degree in computer science, engineering, data or information systems, or a related field. - 8–12+ years in data engineering or architecture, including 3–5+ years architecting cloud data platforms; Google Cloud experience is preferred. - Enterprise data lake, warehouse, and streaming architecture experience, with hands-on knowledge of BigQuery, Cloud Storage, Dataflow, Dataproc, Pub/Sub, and Cloud Composer. - Strong grounding in data modeling, ETL/ELT, change data capture, streaming, and schema evolution, plus experience with Terraform, CI/CD, automated testing, and Git. - Experience with cloud security, governance and lineage, regulated compliance frameworks, and optimization of data platform performance and cost; strong communication and stakeholder skills.

Nice to have Professional cloud architecture or data engineering certifications, government or regulated-industry experience, Kubernetes or OpenShift certifications, and experience with service mesh, API gateways, multi-cluster approaches, or GitOps.