Analytics Engineer, Assistant Vice President (AVP) Data & Applications | New York, NY | Assistant Vice President

This role is not eligible for visa sponsorship. Applicants must have unrestricted authorization to work in the United States.

About the Role

We are looking for a developer with strong analytical instincts who enjoys building data-driven applications and analytics tools used by business teams to make better decisions. This role sits at the intersection of application development, analytics engineering, and data science, where you will work with modern cloud technologies to turn complex financial data into practical, production-ready solutions used across the organization.

You will work primarily in a Python, Databricks, and Snowflake environment on Azure, building internal applications and analytics workflows that enable business teams to explore and act on data more effectively. The ideal candidate is a builder first -- curious, collaborative, and comfortable owning the full product lifecycle from prototype to deployment.

Team Overview

The Data & Applications team develops business-facing applications and builds analytics tools, AI-enabled solutions, and data infrastructure that connect data, technology, and decision-making across the organization. The team combines financial and business expertise with technical capabilities in software development, data engineering, and analytics to deliver scalable technology solutions that support both corporate functions and client advisory teams.

Role Overview

We are seeking a developer who is excited to work at the intersection of AI, application development, and financial services. The ideal candidate is comfortable navigating ambiguity, enjoys solving complex problems involving financial data, and is motivated by shipping modern analytics tools and AI-powered applications that business teams rely on daily.

In this role, you will work closely with client-facing business teams and own projects across the entire application lifecycle -- prototyping, design, testing, deployment, and ongoing support. This is a highly visible position where the solutions you build will directly support teams that actively depend on the tools and insights you deliver.

Responsibilities

• Design, build, and deploy internal applications and analytics solutions that enhance client advisory workflows and improve access to financial data across the organization.
• Partner directly with business stakeholders to translate their needs into practical technical solutions, making informed decisions on architecture, tools, and feasibility.
• Build analytics layers, dashboards, and tools that enable business users to explore, analyze, and act on data independently.
• Integrate LLM APIs and AI capabilities into analytics workflows and internal applications where appropriate.
• Ensure data reliability by managing documentation, quality standards, and monitoring for the pipelines and analytics products you develop.
• Stay current on advancements in AI and analytics technologies and identify opportunities to apply them within financial services workflows.

Qualifications

We are looking for individuals who demonstrate initiative, can work independently, and perform well in a fast-paced, entrepreneurial environment.

• 5+ years of experience in analytics engineering, data-intensive application development, or data science, with a track record of delivering production-ready solutions used by business teams.
• Demonstrated experience building internal tools or applications for business users -- not just dashboards and reports, but full-feel products that stakeholders interact with directly.
• Proficiency in Python and strong SQL skills with hands-on experience in Databricks and Snowflake.
• Experience working in Azure or another major cloud platform (AWS or GCP), with Azure experience strongly preferred.
• Familiarity with CI/CD practices and version control tools such as GitHub or Azure DevOps.
• Knowledge of data modeling concepts and experience transforming raw datasets into clean, well-structured data for analysis.
• Strong communication skills and the ability to work directly with both technical and non-technical stakeholders.

Additional Experience (Strongly Preferred)

• Hands-on experience integrating LLM APIs (such as Anthropic, OpenAI, or Azure OpenAI) into production systems or data workflows.
• Experience with Azure services such as Azure AI, Azure Functions, or Azure OpenAI.
• Previous experience in investment banking, financial services, or a related industry, with familiarity around deal workflows or financial reporting processes.
• Experience using AI-assisted development tools such as GitHub Copilot or Cursor as part of an active development workflow.