AI Summary
Design, maintain, and optimize data models for accurate reporting, transparency, and operational efficiency in the financial services industry.
Key Highlights
Develop and maintain conceptual, logical, and physical data models
Collaborate with senior architects, SMEs, and junior team members
Partner with leadership to resolve design conflicts and align on modeling standards
Technical Skills Required
Benefits & Perks
Long-term contract
Relocation assistance
On-site work in Lake Mary, FL (4 days a week)
Job Description
Dice is the leading career destination for tech experts at every stage of their careers. Our client, Saksoft, is seeking the following. Apply via Dice today!
Position: Sr. Data Modeler
Location: Lake Mary, FL (NO REMOTE - onsite 4x week in Lake Mary) can consider relocation if necessary.
Duration: Long-term contract
Interview: 2-step IV process
Role Summary
The Data Modeler will support Client Alternatives and Banking operations by designing, maintaining, and optimizing data models that enable accurate reporting, transparency, and operational efficiency. This role requires expertise in both traditional and modern modelling approaches (relational and NoSQL/JSON), familiarity with financial services (custody, fund accounting, alternatives), and strong interpersonal skills to navigate complex team interactions. The Data Modeler will collaborate with senior architects, SMEs, and junior team members, ensuring high-quality deliverables while fostering team cohesion and adaptability in agile environments.
Key Responsibilities
- Data Modeling
- Develop and maintain conceptual, logical, and physical data models using tools such as Erwin, Power Designer, SQL Developer Data Modeler, and MagicDraw.
- Deliver NoSQL models using JSON schemas, ensuring compatibility with modern data pipelines and automation-driven approaches.
- Adapt designs dynamically in agile sprint cycles, balancing rigor with flexibility.
- Ensure models align with client requirements, even when multiple proposed models exist (e.g., Model A vs. Model C).
- Collaboration & Governance
- Partner with senior architects, SMEs, and leadership to resolve design conflicts and align on modeling standards.
- Navigate strong opinions constructively, ensuring architecture and team interactions remain integrated.
- Mentor junior data partners, reviewing outputs, guiding growth, and allowing for error margins while maintaining quality.
- Contribute to data governance initiatives, including business glossaries, data quality frameworks, and metadata repositories (e.g., Collibra, FLDM).
- Technical Delivery
- Leverage Python scripting for automation, data transformation, and back-end integration tasks.
- Work with banking/accounting systems (e.g., custody platforms, fund accounting systems such as Incompass) to ensure accurate data flows.
- Support capabilities meetings and provide tailored offerings information to clients when needed.
- Contribute to data pipeline development and automation features.
- Communication & Team Engagement
- Demonstrate strong communication skills to manage disagreements with senior architects and SMEs constructively.
- Maintain team traction and alignment across projects, ensuring collaborative delivery.
- Provide examples of conflict resolution and teamwork that highlight collective outcomes rather than self-promotion.
- Exhibit flexibility in handling healthy challenges, escalation patterns, and team dynamics that are not always visible on resumes but critical in practice.
- Technical Skills
- Proficiency in data modelling tools (Erwin, Power Designer, SQL Developer Data Modeller, Magic Draw).
- Strong knowledge of conceptual, logical, and physical modelling.
- Experience with NoSQL modelling and JSON schemas.
- Familiarity with Python scripting for automation and integration.
- Exposure to data pipelines and automation-driven modelling approaches.
- Governance knowledge: business glossaries, Collibra, data quality frameworks.
- Domain Expertise
- Background in financial services, ideally with exposure to alternative investments (hedge funds, private equity, real estate, managed futures).
- Accounting background preferred: custody accounting, fund accounting, positions, transactions, balances, general ledger, P&L statements, and balance sheets.
- At least 2 3 projects in the banking or investment domain demonstrating applied data modelling.
- Ability to work in agile environments, adapting designs sprint-to-sprint.
- Strong communication skills to manage disagreements with SMEs and architects constructively.
- Team-oriented mindset: avoids excessive self-focus, emphasizes collective outcomes.
- Mentorship ability to support junior team members and foster team cohesion.
- Flexibility to handle healthy challenges, escalation patterns, and dynamic team environments.
- Experienced in both traditional relational modelling and modern NoSQL/JSON schema approaches.
- Comfortable balancing technical rigor with agile improvisation.
- Skilled communicator who can navigate conflicts, mentor juniors, and keep teams aligned.
- Technically versatile, with strong modelling, governance, and scripting skills to support evolving business needs.
- Possesses banking/fund accounting knowledge to complement technical expertise, even if alternatives experience is limited.