Google Cloud Data Modeler / Data Architect

• We are seeking an experienced Google Cloud Data Modeler / Data Architect to design, develop, and govern scalable enterprise data architectures on Google Cloud Platform (Google Cloud Platform).
• The role will be responsible for translating business requirements into robust conceptual, logical, and physical data models and implementing scalable data solutions using Big Query and other Google Cloud Platform data services.
• The ideal candidate will have strong experience in enterprise data modeling, data warehousing, data integration, data governance, data quality, and cloud architecture, with the ability to work closely with business stakeholders, data engineers, analysts, and application teams., Data Architecture:
• Design end-to-end data architecture solutions on Google Cloud.
• Define scalable and secure architectures for data ingestion, transformation, storage, analytics, and reporting.
• Design data lake, data warehouse, and modern Lakehouse architectures.
• Define Google Cloud Platform project, dataset, schema, and data-layer strategies.
• Establish architecture standards, design patterns, and best practices.
• Evaluate existing data platforms and recommend modernization opportunities.

Data Modeling:

• Develop Conceptual, Logical, and Physical Data Models.
• Design enterprise data models covering master data, transactional data, reference data, and analytical data.
• Develop dimensional models including Fact and Dimension tables.
• Design Star and Snowflake schemas where appropriate.
• Define entities, attributes, relationships, keys, constraints, and business rules.
• Develop canonical and semantic data models for enterprise reporting and analytics.
• Maintain data dictionaries, business glossaries, metadata, and lineage.

Google Cloud Platform / BigQuery:

• Design and optimize data models in Google BigQuery.
• Define BigQuery datasets, tables, views, materialized views, and schemas.
• Apply partitioning and clustering strategies for performance and cost optimization.

Design scalable data processing solutions using services such as: *

• BigQuery
• Cloud Storage
• Dataflow
• Dataproc
• Pub/Sub
• Cloud Composer
• Dataplex / Knowledge Catalog
• Cloud SQL

Data Governance & Quality:

• Establish data governance standards and architecture principles.
• Define data ownership, stewardship, classification, and access patterns.
• Implement data quality rules and validation frameworks.
• Define standards for master and reference data.
• Support data lineage, metadata management, and data cataloging.
• Ensure compliance with security, privacy, and regulatory requirements.
• Define appropriate IAM and data-access models.
• Google Cloud’s BigQuery ecosystem includes governance, metadata, lineage, and access-control capabilities that support these responsibilities.

Data Integration & Transformation:

• Define source-to-target mappings.
• Design data ingestion and transformation patterns.
• Develop transformation rules and business logic.
• Define data reconciliation and validation processes.
• Design integration between source systems, Google Cloud Platform, and downstream analytics platforms.
• Work with engineering teams to ensure physical implementations conform to approved architecture and data models.

Business & Stakeholder Collaboration:

• Partner with business stakeholders to understand business processes and data requirements.
• Translate business requirements into technical data architecture.
• Work with data engineers, BI developers, data scientists, and application teams.
• Facilitate architecture and data-model review sessions.
• Communicate complex technical concepts to both technical and non-technical stakeholders., * ER/Studio
• ERwin
• Lucidchart
• Draw.io
• Sparx Enterprise Architect
• SQL Developer Data Modeler
• dbt
• BigQuery Data Modeling tools

Architecture & Design Skills:

The candidate should be able to create and maintain:

Source Systems * Raw/Landing Layer * Curated Layer * Business/Consumption Layer * BI / Analytics

and define:

• Source-to-target mappings
• Data flow diagrams
• Logical data models
• Physical data models
• Data lineage
• Data dictionaries
• Business rules
• Data quality rules
• Integration architecture
• Security architecture
• Data governance framework

Preferred certifications:

• Google Cloud Professional Cloud Architect
• Google Cloud Professional Data Engineer
• Other relevant Google Cloud Platform certifications.

About the Job- We are looking for an experienced Google Cloud Data Modeler / Data Architect to join one of our enterprise client engagements. The ideal candidate should have strong expertise in, BigQuery, SQL, Sparx Enterprise Architect, Dataflow, Google Cloud Platform along with experience working in fast-paced enterprise environments., * 8+ years of experience in data architecture, data modeling, data warehousing, or related areas.

• Strong hands-on experience with Google Cloud Platform.
• Strong BigQuery experience.
• Strong SQL skills.
• Experience with enterprise data modeling.
• Experience with ETL/ELT architecture.
• Experience with data governance and data quality.
• Understanding of master data and reference data management.
• Experience with metadata and data lineage.
• Strong understanding of relational and analytical database concepts.
• Experience developing:

Preferred Google Cloud Platform Skills:

• BigQuery
• Cloud Storage
• Dataflow
• Dataproc
• Pub/Sub
• Cloud Composer
• Dataplex / Knowledge Catalog
• Cloud SQL
• IAM
• Cloud Monitoring
• Terraform / Infrastructure as Code

CodeForce 360 is a trusted global IT talent partner helping Fortune 500 companies, system integrators, and enterprise organizations build high-performing technology teams. With over 16 years of industry expertise, we combine speed, precision, and market intelligence to deliver exceptional talent across today’s most in-demand technologies.