Business Analyst, Senior Associate

About the role

If you're passionate about turning complex data into clear, actionable insights, this is the role for you. Here, you'll work at the intersection of marketing, technology, and analytics — helping shape how data-driven decisions get made across the organization.

Responsibilities

• Collaborate with marketing, operations, and data teams to understand business needs, objectives, and decision workflows impacted by reporting and analytics products.
• Proactively engage end users and key stakeholders to elicit, analyze, and document business requirements, including current-state pain points, future-state needs, and measurable success criteria.
• Facilitate discovery sessions — workshops, interviews, and ride-a-longs — to map business processes, identify reporting gaps, and prioritize enhancements based on business value, risk, and feasibility.
• Translate business requirements into clear technical specifications, including user stories, acceptance criteria, data definitions, report logic, and non-functional requirements.
• Partner with data, engineering, and product teams to identify opportunities to transform reporting through automation, AI-assisted insights, intelligent alerting, and self-service enablement — with appropriate human oversight and operational controls.
• Design and develop data models, pipelines, and visualization dashboards to support standardized, scalable reporting.
• Work with developers and engineers to implement, test, and iterate on data and analytics products, ensuring traceability from stakeholder requirements through build and release.
• Conduct user acceptance testing, validating business logic, reconciling results to source systems, and confirming usability for target audiences.
• Provide change management support and training, including release communications, enablement materials, and adoption feedback loops.
• Monitor data to identify trends and insights, and partner with stakeholders to refine KPIs, reporting cadence, and exception management.
• Develop and maintain documentation for analytics products, including business requirements, data dictionaries, lineage summaries, and runbooks.

Requirements

• Bachelor's degree in Business Administration, Computer Science, Information Systems, or a related field.
• 3 years of experience as a Technical Business Analyst with direct responsibility for requirements elicitation and documentation of business and technical requirements.
• Demonstrated ability to lead stakeholder discussions independently, including facilitating workshops, managing competing priorities, and aligning cross-functional teams on scope and outcomes.
• Strong understanding of data warehousing, data modeling, ETL, and data visualization, with the ability to define requirements that translate into scalable datasets and trusted reporting outputs.
• Experience with SQL and at least one programming language (e.g., Python, SAS), sufficient to validate logic, perform data analysis, and support requirements verification.
• Hands-on experience with data analytics tools and techniques, including Alteryx, Tableau, and Snowflake.
• Proven ability to translate ambiguous business requests into structured deliverables — user stories, process flows, data definitions, and acceptance criteria — with a strong orientation toward measurable outcomes.
• Excellent communication, presentation, and interpersonal skills, with the ability to tailor messaging to end users, technical teams, and leadership stakeholders.
• Able to work independently and collaboratively in an agile environment, including backlog grooming, sprint planning support, and iterative delivery.

Preferred Qualifications

• Experience with marketing platforms such as Salesforce, Adobe Experience Manager, or similar tools.
• Experience with cloud-based data platforms such as AWS, Azure, or Google Cloud Platform.
• Experience with machine learning and artificial intelligence, including translating business problems into AI and automation use cases and defining requirements for AI-assisted reporting and insights.
• Familiarity with agile methodologies and iterative delivery practices.
• Experience with agentic workflow patterns — including automation and orchestration, human-in-the-loop review, and exception handling — and exposure to responsible AI considerations such as explainability, data privacy, and operational controls.