Finance Data Modeler & Transformation Rep
The Finance Data Modeler & Transformation Rep at Confidential Client is responsible for building and maintaining Power BI data models and dashboards, developing automations using Alteryx, and supporting AI and technology initiatives to enhance financial data analytics. This role partners with finance teams to advance data proficiency and supports the evaluation of new technology solutions, contributing to the company's digital transformation efforts in a high-demand defense environment.
About Careertakes
👉 Important disclosure: Careertakes is a third-party recruiting platform supporting this hiring process. If selected, you will be employed directly by our client, IT.
Applicants for this role may also receive access to additional matched opportunities through the Careertakes platform.
Overview
Confidential Client’s Finance Digital Transformation Office (DTO) is expanding its data analytics and automation team. The team enables resilient, interactive financial reporting as the organization scales. This role focuses on building and maintaining data models and visualizations (Power BI), developing automation workflows (Alteryx), and supporting AI- and data-focused initiatives. Candidates from entry-level through mid-career are encouraged to apply.
What You’ll Do
- Build and maintain Power BI data models for financial data analytics.
- Develop Alteryx automations and other processes to strengthen Finance’s analytics infrastructure.
- Create and maintain Power BI dashboards for visualization and reporting.
- Partner with Finance stakeholders to elevate data literacy and transformational thinking.
- Support evaluation and implementation of new technology solutions (including data and AI initiatives).
Required Qualifications
- Bachelor’s degree in data analytics, business, finance, mathematics, statistics, computer science, Information Technology, or a related field.
- 3+ years combined experience in data modeling, data visualization, and/or reporting — OR for entry-level candidates, a data-focused major, advanced degree, or relevant certifications.
- Hands-on experience with Power BI or a closely related visualization tool.
- Demonstrated willingness and ability to learn new software and tools quickly.
Preferred Qualifications
- Experience applying data analytics in financial contexts.
- Experience building automations with Alteryx.
- Experience implementing AI-driven improvements for enterprise data analysis use cases.
- Familiarity with enterprise financial systems (e.g., Oracle, mainframe environments), reporting requirements, or government compliance considerations.
- Advanced degrees or specialized certifications in data analytics, data science, or related fields.
Skills & Tools
- Data modeling and data visualization (Power BI or similar)
- Alteryx (automation/workflow development)
- Financial data reporting and analytics
- MS Office Suite (Excel, Teams, etc.)
- Strong written and verbal communication; collaborative team skills
- Curiosity and eagerness to learn new technologies
Location & Employment Type
- Location: Groton, CT (on-site or local to the Groton area as required by role)
- Employment type: Full-time
Compensation
- Estimated salary (as listed by the source): $71,470 per year (estimated). Exact compensation and benefits will be determined by the Confidential Client and will comply with applicable state and federal requirements.
Note on Employer & Privacy
All references to the hiring organization in this listing appear as "Confidential Client" to protect employer confidentiality. Careertakes may provide matched opportunities and uses applicant data only as described in our privacy policies.
Equal Opportunity & Hiring Transparency
Careertakes and our client are Equal Opportunity Employers committed to building a diverse and inclusive workforce. We prohibit discrimination or harassment of any kind. To support a fair and efficient hiring process, AI tools may be used to assist with application review or resume screening. These tools do not replace human decision-making. Final hiring decisions are made by people.
If you have questions about how your data is used, please contact us directly.
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