We are seeking a skilled professional to join our team in a hybrid onsite role located in Jersey City, NJ, Dallas, TX, or Tampa, FL. This is a 6-month opportunity for local candidates only.Responsibilities
Design scalable data models optimized for cloud-native architecture, including the use of virtual warehouses, clustering keys, and materialized views.
Develop conceptual, logical, and physical data models that align with financial regulatory requirements.
Collaborate with data engineers and architects to implement models that support real-time analytics, fraud detection, and risk management.
Ensure data quality and consistency across diverse financial systems such as trading platforms, customer onboarding, and compliance tools.
Integrate structured and semi-structured data using native capabilities to support complex financial reporting.
Document data lineage and metadata to support auditability and transparency for internal and external stakeholders.
Optimize data storage and query performance using specific features like automatic clustering and query profiling.
Support data governance initiatives by aligning models with enterprise data catalogs, stewardship policies, and access controls.
Collaborate with business analysts and compliance teams to translate financial reporting needs into robust data structures.
Continuously refine models based on evolving financial products, market conditions, and regulatory changes.
QualificationsEducation and Experience
Bachelor's degree in Computer Science, Information Systems, Data Science, or a related field (Master's preferred).
5 years of experience in data modeling, with at least 2 years working with cloud-based solutions in a production environment.
Prior experience in the financial services industry, with familiarity in domains like risk, compliance, trading, or customer analytics.
Technical Skills
Proficiency in designing conceptual, logical, and physical data models.
Strong SQL skills and experience with cloud-specific features.
Familiarity with data modeling tools.
Understanding of data warehousing principles, dimensional modeling, and normalization techniques.
Experience integrating structured and semi-structured data in cloud environments.
Knowledge of financial data structures and regulatory requirements.
Experience working with data governance, metadata management, and data quality frameworks.
Soft Skills
Strong collaboration and communication skills to work with cross-functional teams including data engineers, analysts, and compliance officers.
Ability to translate business requirements into scalable and efficient data models.
Detail-oriented with a focus on data accuracy, consistency, and performance.
