Overview
We are seeking a skilled Technical Business Analyst to join our team for a significant AI and data transformation initiative. In this remote role, the contractor will collaborate closely with operational teams and data engineers to ensure successful data initiatives, from validation to business adoption. The focus will be on driving data governance, gathering requirements, and facilitating user acceptance testing, playing a critical role in enhancing data processes across the organization.
Responsibilities
- Conduct data validation and quality assurance to ensure accuracy and reliability.
- Define and document high-level process taxonomies and conceptual data models.
- Produce detailed test scripts, scenarios, and acceptance criteria for various initiatives.
- Run user acceptance testing (UAT) cycles with subject matter experts while balancing program deadlines.
- Gather and maintain a central repository of business definitions and taxonomies related to finance and operations.
- Collaborate with operational leaders to facilitate business adoption and uphold data governance standards.
- Translate complex business requirements into technical specifications and user stories.
- Map data dependencies and lead workshops to resolve analytical challenges.
Requirements
- Proven experience as a Technical Business Analyst in data migration, warehousing, or BI transformation projects.
- Solid background in data transformation programs, including requirements definition and business adoption.
- Exposure to AI initiatives, particularly in data preparation for machine learning applications.
- Experience designing UAT frameworks, including writing test scripts and managing user validation.
- Hands-on expertise in capturing process taxonomies and developing data dictionaries.
- Strong communication skills across different functions, particularly in finance or FP&A settings.
- Familiarity with Agile/Scrum methodologies and tools such as Jira and Confluence.
- Desirable experience with enterprise reporting frameworks, Common Data Models, or BI tools like Databricks.