Data Modeler

Trail Blazer Consulting LLC

Malvern, PA, United States

21 days ago

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Role details

Contract type

Temporary to permanent

Employment type

Full-time (> 32 hours)

Experience level

Expert

Experience required

8 years minimum

Working hours

Regular working hours

Job source

www.dice.com

Tech stack

Amazon Web Services Audit Trail Microsoft Azure Big Data Databases Data Architecture Information Engineering Data Governance Data Integrity Extract Transform Load (ETL) Relational Databases Meta-Data Management

+9 more

Microsoft SQL Server Reference Data Cloud Services Sql Optimization Snowflake Data Lineage Star Schema Physical Data Models Data Pipelines

Job description

Design, develop, and maintain conceptual, logical, canonical, and physical data models, including ERDs and dimensional/star schemas, to support asset management, wealth management, and financial advisory platforms.
Partner with business stakeholders, data engineers, solution architects, and technical teams to translate complex financial domain requirements into scalable, enterprise data models.
Model data across key financial subject areas, including financial profiles, advisor teams, securities, holdings, portfolio performance, and risk analytics.
Apply data modeling best practices, including normalization, slowly changing dimensions (SCD), data lineage, metadata management, and reference data governance.
Develop and optimize data models across relational databases, cloud platforms, and big data environments such as Snowflake, SQL Server, AWS, and Azure.
Ensure data models comply with financial services regulatory requirements, including data privacy, auditability, and reference data integrity.
Collaborate with ETL and data engineering teams to validate source-to-target mappings, troubleshoot data quality issues, and support reporting and analytics initiatives.

Requirements

8+ years of experience in enterprise data modeling and data architecture.
Proven experience within investment management, asset management, wealth management, or broader financial services environments.
Strong understanding of conceptual, logical, canonical, and physical data modeling methodologies.
Hands-on experience designing dimensional (star schema) and normalized relational data models.
Advanced SQL skills with the ability to analyze, validate, and optimize complex datasets.
Proficiency with enterprise data modeling tools such as Erwin, ER/Studio, Hackolade, or similar platforms.
Experience working with cloud data platforms and databases, including Snowflake, SQL Server, AWS, and Azure.
Knowledge of data governance, metadata management, data lineage, and slowly changing dimension (SCD) concepts.
Experience partnering with cross-functional teams to translate business requirements into scalable data solutions.
Familiarity with financial services regulatory and compliance requirements related to data privacy, audit trails, and data integrity.