GCP Data Modeler – Banking Domain

VSG Business Solutions•Charlotte, NC

About The Position

We are seeking an experienced GCP Data Modeler with strong expertise in data modeling, cloud data platforms, and the banking/financial services domain. The ideal candidate will be responsible for designing conceptual, logical, and physical data models for enterprise-scale data platforms on Google Cloud Platform (GCP). The candidate will work closely with data architects, engineers, business stakeholders, and application teams to translate complex banking requirements into scalable and governed data solutions.

Requirements

10+ years of experience in data modeling, database design, or data architecture.
Strong hands-on experience with GCP data technologies, particularly BigQuery.
Strong knowledge of conceptual, logical, and physical data modeling.
Experience with dimensional modeling, Star Schema, Snowflake Schema, and 3NF.
Strong SQL skills and experience working with large enterprise datasets.
Strong understanding of data warehousing, data lakes, and modern cloud data architectures.
5+ years of experience in banking or financial services.
Strong understanding of banking data domains, business processes, and terminology.
Experience with data modeling tools such as ER/Studio, ERwin, or similar tools.
Experience creating source-to-target mappings and data dictionaries.
Strong understanding of data governance, data quality, metadata, and data lineage.
Excellent communication and stakeholder-management skills.

Responsibilities

Design and maintain conceptual, logical, and physical data models for enterprise banking applications and data platforms.
Develop scalable data models for GCP-based data warehouses, data lakes, and analytical platforms.
Work extensively with Google BigQuery and cloud-based data architecture.
Analyze business requirements and translate them into robust data structures and models.
Develop data models supporting banking functions such as: Retail and commercial banking, Customer and account management, Deposits and lending, Payments and transactions, Credit and risk, Regulatory reporting, Fraud and AML.
Define entities, attributes, relationships, keys, constraints, and business rules.
Establish and maintain enterprise data modeling standards and naming conventions.
Collaborate with data architects and engineers to ensure models are optimized for performance, scalability, and maintainability.
Support data warehouse and data lake design using dimensional modeling techniques such as Star and Snowflake schemas.
Perform source-to-target mapping and assist with data integration and ETL/ELT design.
Work with data governance teams to support data quality, lineage, metadata, and master/reference data management.
Identify data redundancies, inconsistencies, and gaps and recommend appropriate solutions.
Optimize physical data models for BigQuery and other GCP data services.
Create and maintain data model documentation and metadata.
Participate in architecture reviews, technical discussions, and Agile ceremonies.
Provide guidance and mentoring to data engineers and development teams.