Data Platform Analyst III

GAINSCO•Richardson, TX

1d•Hybrid

About The Position

GAINSCO is seeking a senior individual contributor to translate complex business and data needs into clear requirements for enterprise data solutions. The role partners with business stakeholders, Data Engineering, Architecture, Governance, and Analytics teams to support data initiatives from discovery through deployment. The analyst evaluates data sources, processes, integrations, and reporting needs, helping teams deliver scalable, reliable, business-aligned solutions. The position combines advanced business analysis skills with strong data knowledge, cross-functional leadership, and effective communication with both business and technical audiences. The analyst also mentors analysts and cross-functional partners and helps improve data literacy, documentation standards, and data platform analysis practices.

Requirements

High school diploma or equivalent required.
At least 5 years of experience in business analysis, data analysis, data platform delivery, project management, or a related field.
At least 1 year of experience in the Property & Casualty (P&C) insurance or financial services industry.
Experience gathering complex business and data requirements and translating them into functional and technical requirements, user stories, acceptance criteria, and source-to-target specifications.
Experience supporting data platform, data integration, modernization, or analytics initiatives throughout the delivery lifecycle.
Experience analyzing source systems, data structures, integrations, transformations, reporting needs, and data-quality requirements.
Experience facilitating discovery sessions and coordinating testing, data validation, defect resolution, and stakeholder approval.
Experience supporting enterprise data solutions involving technologies such as Azure data services, Snowflake, Airflow, Kafka, Fivetran, or Power BI.
Experience managing multiple stakeholders, requirements, risks, dependencies, assumptions, and competing priorities.
Experience mentoring analysts, delivery partners, or business stakeholders on data practices and requirements standards.
Advanced skills in requirements elicitation, data analysis, process mapping, user story development, and acceptance criteria.
Advanced proficiency with SQL and working knowledge of relational and dimensional data concepts.
Ability to create visual representations of data flows, system integrations, lineage, platform interactions, and business processes.
Working knowledge of data quality, metadata, lineage, master and reference data, reporting requirements, security classifications, and data governance.
Strong facilitation and stakeholder-management skills, including the ability to align business and technical teams.
Ability to explain complex data and technology concepts in clear, actionable business language.
Strong problem-solving and decision-making skills, including identifying risks, dependencies, data issues, and control requirements early in delivery.
Ability to influence without direct authority and guide cross-functional teams toward shared outcomes.
Strong written, verbal, presentation, and mentoring skills.
Must be eligible to lawfully work in the U.S. immediately; the employer will not sponsor U.S. work authorization.
Offers are contingent on satisfactory background investigation results and a pre-employment drug test.

Nice To Haves

Bachelor’s degree in Information Systems, Data Analytics, Computer Science, Business, or a related field preferred.
Experience in Personal Auto insurance preferred.
At least 2 years of experience supporting complex, cross-functional data or technology initiatives preferred.

Responsibilities

Lead discovery sessions and translate business and data needs into requirements, user stories, acceptance criteria, and source-to-target specifications.
Partner with business and technical teams throughout planning, design, development, testing, deployment, and transition to production support.
Document data flows, process workflows, integrations, business rules, lineage, ownership, quality expectations, and reporting requirements.
Manage the requirements backlog, track risks and dependencies, and resolve requirement gaps or ambiguities.
Coordinate data validation, reconciliation, defect triage, User Acceptance Testing, and stakeholder approval.
Mentor analysts and cross-functional partners and improve data literacy, documentation standards, and data platform analysis practices.