Sr. Data Analyst/Data Modeler - Wealth & Financial Services

About the position

Are you an experienced Data Analyst or Data Modeler who thrives at the intersection of complex data ecosystems and high‑impact business domains? Trissential is partnering with our client—a leading organization within the Wealth & Financial Services sector—to bring on a seasoned data professional who can help shape the future of enterprise data architecture, governance, and quality. I f you enjoy influencing data strategy, elevating data standards, and translating intricate business processes into trusted, governed, high‑quality data models, this opportunity is tailored for you.

What’s in It for You?

Meaningful industry impact – contribute directly to data architecture supporting Wealth, Investment, and broader Financial Services operations

Strategic influence – collaborate across business, analytics, engineering, and governance teams to drive enterprise‑level data decisions

Modern data ecosystem – work with Snowflake, Python data profiling, metadata management, and modeling tools

Career growth – expand your modeling expertise while shaping data products and evolving enterprise data standards

Trusted seat at the table – your expertise helps guide data quality, alignment, lineage, and governance in a highly regulated industry

Your Role & Responsibilities

You will:

Support the full end‑to‑end data modeling lifecycle across a dynamic Financial Services domain.

Partner with Wealth/Investment business stakeholders and Product Owners to map conceptual models that reflect real‑world financial processes and terminology

Design logical data models including entities, attributes, relationships, and constraints aligned to Financial Services datasets

Translate logical models into physical schemas for relational, columnar, and lakehouse environments

Execute detailed data profiling to evaluate quality, identify anomalies, and quantify core data quality metrics

Support model‑to‑source and model‑to‑target data mapping

Validate physical model performance, scalability, and security—especially within regulated FS environments

Maintain data dictionaries, lineage documentation, and metadata artifacts

Partner with Data Governance teams to align taxonomy, naming standards, and quality controls

Participate in design reviews, change management workflows, and governance forums

Provide impact analysis for structural or semantic data changes affecting Wealth/Investment datasets

Responsibilities

• Support the full end‑to‑end data modeling lifecycle across a dynamic Financial Services domain.
• Partner with Wealth/Investment business stakeholders and Product Owners to map conceptual models that reflect real‑world financial processes and terminology
• Design logical data models including entities, attributes, relationships, and constraints aligned to Financial Services datasets
• Translate logical models into physical schemas for relational, columnar, and lakehouse environments
• Execute detailed data profiling to evaluate quality, identify anomalies, and quantify core data quality metrics
• Support model‑to‑source and model‑to‑target data mapping
• Validate physical model performance, scalability, and security—especially within regulated FS environments
• Maintain data dictionaries, lineage documentation, and metadata artifacts
• Partner with Data Governance teams to align taxonomy, naming standards, and quality controls
• Participate in design reviews, change management workflows, and governance forums
• Provide impact analysis for structural or semantic data changes affecting Wealth/Investment datasets

Requirements

• 10+ years of experience in data analysis, data modeling, or advanced data roles
• Strong expertise in conceptual, logical, and physical data modeling
• Proven experience in Financial Services—ideally Wealth, Asset Management, Investments, or Banking
• Ability to translate business requirements into precise, structured data artifacts
• Proficiency with SQL and analytical data investigation
• Experience with data profiling and data quality frameworks
• Working knowledge of data governance, metadata management, and lineage
• Strong communication skills across both technical and business audiences

Nice-to-haves

• Snowflake experience
• Python data profiling experience
• Ability to parse or interpret JSON, COBOL, JCL, SQL, Java, C/C++, or .NET
• ERWIN experience for ERDs, forward engineering, and reverse engineering
• Exposure to naming standards enforcement or data cataloging initiatives

Benefits

• Comprehensive Benefits for you and your dependents – Medical, dental, vision, free tele-health, HSA with company contribution, life and disability insurance, and 401k with matching
• Paid Time Off – Both compensation models offer paid time away from work
• Hybrid work flexibility with up to 3 days onsite in Minneapolis
• Career development opportunities through mentorship, hands-on learning, and leadership engagement
• Inclusive, supportive team culture built around integrity, collaboration, and professiona