Senior Associate, Solution Analyst Data Warehousing

New York Life Insurance•Tampa, FL

2d•Hybrid

About The Position

As a Solution Analyst on New York Life Direct’s Data Warehousing team, you will analyze, design, and deliver complex enterprise data warehousing and business intelligence solutions. You will independently lead requirements analysis and solution design, translating complex business needs into scalable technical solutions and recommending approaches aligned with business priorities, data architecture standards, and long-term technology objectives. The role calls for independent judgment to resolve ambiguous requirements, address complex delivery challenges, and improve solution quality and team effectiveness. You will partner with stakeholders, data engineers, and architects to shape and validate solutions; lead complex initiatives from intake through delivery; investigate data issues using advanced SQL; and provide technical and functional guidance to engineering teams and colleagues. The position uses AI-enabled and AI-assisted tools to improve efficiency and delivery practices. This is a hybrid position based in Tampa, Florida. Employees work onsite at the New York Life Tampa office Tuesday through Thursday and remotely Monday and Friday.

Requirements

Significant experience in solution analysis, business systems analysis, technical business analysis, or a related IT delivery role, including complex cross-functional initiatives.
Advanced ability to translate complex business needs into functional and technical specifications, user stories, acceptance criteria, and data mappings.
Deep knowledge of enterprise data warehousing, data integration, data pipelines, and business intelligence, including related architecture and governance considerations.
SQL expertise for complex data investigation, source-system analysis, transformation validation, and solution evaluation.
Demonstrated ability to assess solution alternatives, identify dependencies, and recommend approaches to complex business and technical problems.
Experience independently leading discovery sessions, facilitating cross-functional solution discussions, and influencing stakeholder alignment.
Strong understanding of Agile delivery, backlog management, and coordination of multiple complex initiatives.
Ability to exercise independent judgment and resolve complex challenges with limited guidance.
Hands-on experience with AI-assisted development tools such as GitHub Copilot or Claude Code.
Strong analytical, communication, problem-solving, and stakeholder management skills.

Nice To Haves

Experience with ETL, enterprise data modeling, source-to-target mappings, and complex data integration architectures.
Knowledge of enterprise data architecture, data governance, data quality, and related best practices.
Experience improving solution analysis, requirements management, and technology delivery processes.
Experience with Agile work management tools, preferably Jira.
Experience in financial services or insurance.
Bachelor’s degree in Computer Science, Information Systems, Business, Engineering, or a related field, or equivalent practical experience.

Responsibilities

Lead complex requirements analysis and solution design for enterprise data warehousing, integration, and business intelligence initiatives, producing functional and technical specifications, user stories, acceptance criteria, and source-to-target mappings.
Partner with business stakeholders, data engineers, and architects to evaluate solution alternatives and recommend scalable approaches aligned with enterprise architecture and data governance standards.
Facilitate cross-functional discovery and design discussions, resolve conflicting requirements, assess technical feasibility, and build stakeholder alignment.
Drive analysis and coordination of complex initiatives from intake through delivery, using AI-enabled tools to improve efficiency, identify risks and dependencies, and recommend adjustments to support roadmap execution.
Use advanced SQL and analytical techniques to investigate data issues, evaluate source systems, validate transformations, and recommend data quality and integration improvements.
Serve as a technical and functional resource for engineering teams by resolving complex implementation questions and providing detailed requirements and documentation.
Lead requirements validation and solution acceptance activities, evaluate outcomes against business objectives, and address gaps with technical teams.
Recommend improvements to analysis, requirements management, and delivery practices; use AI-assisted development tools and specification-driven approaches to streamline workflows.
Provide functional guidance and share knowledge with colleagues, contributing to consistent team practices.