This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Principal GCP Data Architect based in the United States.
This is a hands-on principal-level architecture role focused on designing and scaling enterprise data ecosystems entirely within Google Cloud Platform.
You will define long-term data platform strategy while leading complex, enterprise-scale migrations and modernizing data architecture for PB-scale workloads.
The role combines deep data engineering expertise with strong capabilities in cloud architecture, governance, security, infrastructure automation, analytics, and AI.
You will architect self-service platforms that empower decentralized teams while maintaining enterprise-wide standards for security, quality, governance, and reliability.
Working closely with engineering, security, business, and executive stakeholders, you will translate complex technical initiatives into measurable business value.
You will also lead and mentor large cross-functional teams, establish architectural standards, and drive continuous improvement across the data organization.
This opportunity is well suited to an experienced GCP specialist who brings strategic vision, hands-on technical depth, and a proven record of leading large-scale cloud transformation.
Accountabilities:
- Define the long-term roadmap and architectural strategy for enterprise data platforms on Google Cloud, ensuring alignment with broader business objectives and strategic data initiatives.
- Design and oversee modern, self-service data architectures that enable decentralized teams while maintaining centralized standards for governance, security, data quality, and operational consistency.
- Lead complex, end-to-end enterprise cloud migrations, including large-scale migrations from AWS to GCP.
- Architect and implement highly scalable data ecosystems capable of supporting petabyte-scale workloads and demanding enterprise use cases.
- Establish robust data governance and security frameworks covering IAM, VPC Service Controls, data masking, encryption, and automated governance capabilities.
- Drive Infrastructure as Code practices using Terraform or Pulumi to create scalable, repeatable, version-controlled cloud infrastructure.
- Architect solutions across the GCP data ecosystem, including BigQuery, BigLake, BigQuery Omni, Google Cloud Storage, Dataflow, Dataproc, Cloud Composer, Pub/Sub, and related services.
- Enable modern analytics and AI capabilities through technologies such as Looker, Vertex AI, and BigQuery ML.
- Architect and integrate messaging and streaming solutions using Pub/Sub and platforms such as Confluent and Kafka.
- Establish modern data engineering practices using dbt, Airflow, Apache Beam, and containerized technologies such as GKE and Kubernetes.
- Lead and mentor large, cross-functional engineering teams operating within Agile and DevOps environments.
- Collaborate with data engineers, software engineers, security specialists, business stakeholders, and technical leadership to deliver scalable and secure data solutions.
- Serve as a trusted technical advisor to executive stakeholders, communicating architectural decisions, technical risks, investment priorities, and expected business outcomes.
- Define enterprise architecture standards, engineering best practices, and continuous improvement initiatives across data platforms.
- Communicate the business value and ROI of major data initiatives while proactively identifying and mitigating technical and operational risks.
Requirements:
- Bring at least 18–20 years of professional experience across data engineering, data warehousing, and business intelligence.
- Have at least 6 years of dedicated experience working with Google Cloud Platform.
- Have worked exclusively with GCP within your relevant cloud experience.
- Hold an active Google Cloud Professional Data Engineer certification.
- Demonstrate expert-level proficiency across the GCP data stack, including BigQuery, BigLake, BigQuery Omni, Google Cloud Storage, Dataflow, Apache Beam, Dataproc, Spark, Hadoop, Cloud Composer, Airflow, and Pub/Sub.
- Have experience integrating Confluent and Kafka with enterprise data platforms and streaming architectures.
- Demonstrate strong knowledge of Looker, Vertex AI, and BigQuery ML for analytics and AI use cases.
- Bring deep experience with modern data engineering technologies such as dbt, Airflow, GKE, and Kubernetes.
- Have successfully led at least two enterprise-scale, petabyte-scale cloud migrations.
- Demonstrate strong expertise in enterprise data platform architecture, data governance, cloud security, and scalable data engineering.
- Have hands-on experience implementing Infrastructure as Code using Terraform, Pulumi, or comparable technologies.
- Demonstrate experience leading and mentoring large, cross-functional engineering teams within Agile and DevOps environments.
- Possess strong executive communication, stakeholder management, and technical advisory skills, with the ability to explain complex architecture and business value to senior leadership.
- Hold a bachelor’s or master’s degree in Computer Science, Information Systems, or a related technical discipline.
- Be a U.S. Citizen or Green Card Holder.
Benefits:
- Annual compensation of $160,000–$220,000.
- Full-time employment.
- Remote work opportunity within the United States.
- Opportunity to work on large-scale enterprise data architecture and cloud transformation initiatives.
- Exposure to advanced GCP technologies spanning data engineering, analytics, AI, streaming, governance, and cloud infrastructure.
- Opportunity to influence enterprise-wide architecture standards and long-term data platform strategy.
- Significant technical leadership and mentoring responsibilities across cross-functional engineering teams.
- Collaboration with senior technical and executive stakeholders on high-impact data initiatives.
How Jobgether works:
We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.
We appreciate your interest and wish you the best!
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