GCP Data Architect

GCP Data Architect

About the role

As a GCP Data Architect, you will make an impact by designing and delivering scalable, cloud-native data platforms that enable enterprise analytics, reporting, and AI-driven business capabilities. You will be a valued member of the Data & Analytics team and work collaboratively with data engineers, data scientists, business analysts, architects, DevOps teams, product owners, and cross-functional technology teams to build secure, high-performing, and innovative data solutions on Google Cloud Platform (GCP).

In this role, you will:

• Design and architect end-to-end enterprise data platforms on Google Cloud Platform (GCP) utilizing services such as BigQuery, Cloud Storage, Dataflow, Dataproc, Pub/Sub, and Cloud Composer to support analytics, reporting, and advanced data use cases.
• Define and implement enterprise data architecture strategies, including data lake and data warehouse architectures, data modeling standards, domain-driven design, and data mesh frameworks.
• Architect scalable batch and real-time data pipelines with a strong focus on performance, reliability, maintainability, and cost optimization through partitioning, clustering, workload management, and resource optimization techniques.
• Establish and enforce data governance, quality, security, metadata management, and lineage frameworks using capabilities such as Dataplex, Data Catalog, IAM, encryption, and data observability tools.
• Collaborate with data engineering, analytics, and machine learning teams to ensure data platforms effectively support business intelligence, reporting, self-service analytics, and AI/ML initiatives.

Work Model

We strive to provide flexibility wherever possible. Based on this role’s business requirements, this is a remote position open to qualified applicants in the United States. Regardless of your working arrangement, we are here to support a healthy work-life balance though our various wellbeing programs.

The working arrangements for this role are accurate as of the date of posting. This may change based on the project you’re engaged in, as well as business and client requirements. Rest assured; we will always be clear about role expectations.

What you need to have to be considered

• 10+ years of experience in Data Architecture, Data Engineering, Data Warehousing, or Cloud Data Platform development.
• Strong experience designing and implementing enterprise-scale data architectures on Google Cloud Platform (GCP).
• Expertise with GCP data services including BigQuery, Cloud Storage, Dataflow, Dataproc, Pub/Sub, Cloud Composer, and related platform capabilities.
• Deep understanding of modern data architecture concepts including data lakes, data warehouses, data mesh, data fabric, and domain-driven architecture principles.
• Experience designing and optimizing batch and real-time data processing pipelines for large-scale data environments.
• Strong knowledge of data modeling methodologies including conceptual, logical, and physical data modeling.
• Experience implementing enterprise data governance, metadata management, data quality, lineage, and security frameworks.
• Proficiency with SQL and data integration technologies, including ETL/ELT design patterns and best practices.
• Experience integrating cloud data platforms with source systems, APIs, third-party applications, and enterprise ecosystems.
• Strong understanding of cloud security principles including IAM, encryption, data protection, compliance, and access governance.
• Experience collaborating with analytics, business intelligence, and machine learning teams to enable data-driven decision-making.
• Strong communication, leadership, and stakeholder management skills with the ability to present architectural solutions and influence enterprise technology decisions.

These will help you stand out

• Google Cloud Professional Data Engineer, Professional Cloud Architect, or related cloud certifications.
• Experience supporting AI/ML, Generative AI, and advanced analytics workloads on GCP.
• Knowledge of Dataplex, Data Catalog, data lineage, observability, and enterprise governance solutions.
• Experience designing and implementing data mesh or domain-oriented data platform architectures.
• Familiarity with data visualization and BI platforms such as Tableau, Looker, Power BI, or similar tools.
• Experience with performance tuning and cost optimization strategies within BigQuery and other GCP services.
• Knowledge of regulatory and compliance requirements related to enterprise data management and governance.
• Experience leading architecture reviews, establishing standards, and mentoring data engineering teams.
• Experience working in Agile environments and delivering large-scale cloud modernization initiatives.
• Background in Financial Services, Healthcare, Insurance, Retail, or other data-intensive industries.

We're excited to meet people who share our mission and can make an impact in a variety of ways. Don't hesitate to apply, even if you only meet the minimum requirements listed. Think about your transferable experiences and unique skills that make you stand out as someone who can bring new and exciting things to this role.

Salary and Other Compensation:

Applications will be accepted until August 22, 2026.

The annual salary for this position is between $100,000 - $170,000 depending on experience and other qualifications of the successful candidate.

This position is also eligible for Cognizant’s discretionary annual incentive program, based on performance and subject to the terms of Cognizant’s applicable plans.

Benefits:

Cognizant offers the following benefits for this position, subject to applicable eligibility requirements:

• Medical/Dental/Vision/Life Insurance
• Paid holidays plus Paid Time Off
• 401(k) plan and contributions
• Long-term/Short-term Disability
• Paid Parental Leave
• Employee Stock Purchase Plan

Disclaimer:

The salary, other compensation, and benefits information is accurate as of the date of this posting. Cognizant reserves the right to modify this information at any time, subject to applicable law.