Analytics Engineering Associate

Prime Finance; New York (NY); On-site; USD 64,000 - 96,000; Full time

Job summary

Prime Finance is seeking an Analytics Engineering Associate in New York to develop and maintain Power BI solutions and governed data products across Investments, Accounting, and Operations.

You will translate business needs into scalable reporting, collaborate with stakeholders, and contribute to data governance, quality, and AI-enabled workflows. This is an on-site role with four days in the New York office.

Qualifications

• Bachelor's degree or relevant work experience.
• 2–5 years in analytics engineering, data analysis, or BI development.
• Proficiency in Power BI, including Power Query and DAX.

Responsibilities

• Build and maintain semantic models and certified datasets on Microsoft Fabric.
• Develop Power BI reports and dashboards across Investments, Accounting, Operations.
• Apply Power Query and DAX for transformations, measures, and row-level security.

Skills

Power BI

SQL

Data modeling

Fabric

AI tools validation

Education

Bachelor's degree in Business/IT/Data Science

Tools

Power BI (Pro)

Microsoft Fabric

dbt

Job description

Prime Finance, founded in 2008, is a well-established, diversified commercial real estate credit investment platform with more than $15 billion in assets under management. Prime Finance has two primary lending strategies that structure financing solutions ranging in size from $10 to $200+ million with teams in San Francisco, Chicago, and New York that originate loans and provide capital across the commercial real estate spectrum. In addition to our lending programs, Prime Finance is an active investor in investment grade and below-investment grade CMBS both at original issuance and on the secondary market.

Job Summary:

Prime Finance is a commercial real estate financing company dedicated to leveraging data and AI to drive innovation, scalability and operational efficiency across the firm. As our Data & AI capabilities continue to evolve, we are growing our Analytics Engineering function focused on developing the reporting, analytics, and governed data products that support decision-making across Investments, Accounting, Operations and other firm teams. This function serves as the bridge between business reporting, data platforms, and future AI-enabled workflows by building reliable semantic models, trusted datasets, and scalable analytics solutions.

The Analytics Engineering Associate will partner closely with the Analytics Engineer and stakeholders across the business to develop and maintain Power BI solutions, semantic models, certified datasets, and other foundational data products on Microsoft Fabric. This role supports data governance, reporting modernization, and the continued development of analytics capabilities that improve data accessibility, reporting consistency, and operational efficiency across the firm.

The ideal candidate is a collaborative and technically curious data professional who enjoys translating business needs into scalable reporting and analytics solutions. They are comfortable working with both technical and non-technical stakeholders, possess strong analytical and problem-solving skills, and maintain a high level of attention to detail. This role is well suited for an early-career analytics professional seeking to deepen their expertise in analytics engineering, data modeling, governance, and AI-enabled data products while contributing to a growing and evolving Data & AI function.

Essential Functions:

• Build and maintain semantic models and certified datasets on Microsoft Fabric.
• Develop Power BI reports and dashboards aligned with business requirements across Investments, Accounting, and Operations.
• Apply Power Query and DAX to implement transformations, measures, and row-level security.
• Support data transformation across established medallion-layer patterns, including notebooks, stored procedures, scheduling, and version control.
• Assist in converting legacy Excel-based reporting to governed Power BI reports.

AI Assisted Delivery

• Use approved AI tools and agents to accelerate routine work (e.g., documentation, first-pass checks, and code drafts), providing the context and constraints needed to get reliable results.
• Validate AI-generated output against source data, identify inconsistencies, and elevate potential quality or reliability issues.
• Own results regardless of how they get produced, applying the same review standard to AI-assisted work as to work done by hand.

AI Data Readiness (supporting)

• Maintain metadata, business glossaries, and documentation for certified datasets so data is accurate and retrieval-ready.
• Support the Analytics Engineer in building taxonomies and semantic documentation.
• Test Data Agent responses against source data and flag gaps or errors, applying the same verification discernment used elsewhere in the role.

Stakeholder Collaboration

• Work with the Analytics & Reporting team and business users to gather requirements and keep developed assets aligned with evolving needs.
• Provide light training and support to business users on self-service data products and reporting tools.

Data Quality & Governance

• Ensure accuracy, consistency, and documentation across reports, models, and transformation logic.
• Follow and contribute to data governance, quality, and certification standards.
• Document business definitions, data relationships, lineage, and assumptions for certified datasets so downstream users and AI-enabled workflows can interpret data consistently.

Qualifications:

• Bachelor's degree in Business Administration, Information Technology, Data Science, or a related field, or relevant work experience.
• 2–5 years of experience in analytics engineering, data analysis, or BI development.
• Proficiency in Power BI, including Power Query and DAX.
• Experience with SQL and data modeling concepts (star/snowflake schema, semantic layers).
• Familiarity with Microsoft Fabric or a comparable modern analytics platform.
• Experience developing and maintaining semantic models and calculated measures.
• Comfort using AI tools responsibly, with strong attention to verifying and validating outputs.
• Strong attention to detail and a collaborative, adaptable approach.
• Exposure to dbt or similar transformation frameworks, and to medallion architecture is preferred.
• Exposure to metadata, business glossaries, taxonomies, or other AI-ready data concepts is preferred.
• Experience in private equity/credit, hedge funds, real estate, investment management, investor relations, or related sectors is preferred.
• PL-300 (Power BI Data Analyst) or DP-600 (Microsoft Fabric Analytics Engineer) certification or equivalent is preferred.

Logistical Requirements (logistical requirements are subject to change based on business need but are anticipated to be):

• Ability to work four full business days a week in Prime's New York office.
• Ability to travel to conferences and other Prime offices up to 20%.

Please note this job description is not designed to cover or contain a comprehensive list of every activity, duty, or responsibility that is required of the employee for this job. Duties, responsibilities, and activities may change at any time with or without notice.

The expected annual base salary range for this role is $64,000 - $96,000. Actual base salary will be determined by several components, including but not limited to: relevant experience, skills and qualifications, base salary of internal peers, and geographic location. In addition to base salary, this role may be eligible for a discretionary annual bonus and a variety of financial, wellbeing, and health / welfare benefits.

Equal Opportunity Employer:

Prime Finance provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state, or local laws. This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation, and training.