Data Architect, Google Cloud Platform (GCP)

West Monroe•Washington, DC

2d•$152,200 - $205,900•Hybrid

About The Position

West Monroe is seeking a Data Architect to design and deliver scalable, cloud-based data solutions for clients. As a technical delivery leader, this role guides engineering teams, advises client stakeholders, and shapes data modernization solutions that deliver measurable business value. The position focuses on Google Cloud Platform (GCP), with BigQuery as a core analytics and data warehousing technology. The role leads technical design across data ingestion, transformation, storage, modeling, governance, orchestration, and consumption. It guides engineering teams through technical specifications, design execution, testing, and implementation, and advises clients on modernizing legacy platforms and migrating workloads to GCP. The architect also supports business development as a technical subject matter expert, translating client challenges into solution architectures and proposals, and contributes to practice development through reusable architectures, standards, mentoring, and knowledge sharing. The role uses AI tools and technologies to accelerate analysis, improve delivery efficiency, generate insights, and support client recommendations, while applying sound judgment to evaluate accuracy, mitigate bias, and ensure high-quality outputs. It is hybrid, with two days per week in the office, and requires frequent travel to New York City for client work every other week. Applicants must be able to work permanently in the United States without sponsorship.

Requirements

At least 7 years of experience in data engineering, data architecture, cloud architecture, or related technology roles, including experience delivering enterprise data solutions.
Deep hands-on expertise with Google Cloud Platform and BigQuery, including data modeling, performance optimization, security, and cost management.
Experience with relevant GCP data services such as Cloud Storage, Dataflow, Dataproc, Pub/Sub, Cloud Composer, or Dataform.
Experience designing batch and/or streaming data pipelines and modern cloud data architectures.
Strong knowledge of SQL, data modeling, ETL/ELT patterns, data governance, and data quality practices.
Ability to communicate architecture decisions and tradeoffs to technical teams and business stakeholders.
Experience integrating AI tools, such as ChatGPT, into day-to-day workflows to enhance productivity and insight generation, with critical thinking to assess accuracy, mitigate bias, and ensure high-quality outputs.
Ability to work permanently in the United States without sponsorship.

Nice To Haves

Google Cloud Professional Data Engineer or Professional Cloud Architect certification.

Responsibilities

Architect scalable, secure, and high-performing GCP data platforms, using BigQuery as a core analytics and data warehousing technology.
Lead technical design across data ingestion, transformation, storage, modeling, governance, orchestration, and consumption.
Design BigQuery data models, optimization strategies, and architectures that balance performance, scalability, security, and cost.
Guide engineering teams through technical specifications, design execution, testing, and implementation while maintaining delivery quality.
Advise clients on modernizing legacy data platforms and migrating data workloads to GCP.
Use AI tools to accelerate analysis, synthesize complex information, and support data-driven client recommendations.
Apply AI technologies, including generative AI, automation tools, and data models, to improve insights, delivery efficiency, and client outcomes.
Serve as a technical subject matter expert in pursuits involving GCP, BigQuery, cloud data modernization, analytics, and AI.
Translate client challenges into solution architectures, estimates, technical approaches, and proposal content.
Identify opportunities to expand data and cloud solutions within existing client relationships.
Develop reusable reference architectures, accelerators, standards, and delivery methodologies for GCP and BigQuery.
Share technical expertise and mentor colleagues to strengthen cloud data architecture and engineering capabilities.
Stay current on Google Cloud capabilities and emerging data, analytics, and AI technologies.