Data & Analytics Specialist

Data & Analytics Specialist

Major Tasks Purpose

The Data & Analytics Specialist is a hands-on operational role responsible for supporting the reliable, accurate, and timely flow of data that powers business decisions, commercial intelligence, and AI enablement. The role focuses on the execution of data quality tasks, vendor feed monitoring, reporting support, business rule maintenance, and process documentation — contributing to the team’s ability to deliver trusted, activation-ready data at scale.

This role reflects the evolution of the traditional business data analyst, moving beyond static reporting toward ensuring that data flows, quality, and structure are robust enough to support both human decision-making and AI-driven intelligence.

The specialist supports day-to-day data operations, including analytics requests, business rule updates, issue resolution, and vendor feed coordination, while building capability in making data AI-ready and leveraging AI tools in daily operations. The role develops business context by learning what the data means commercially, while also building the technical fluency needed to work across platforms, taxonomies, and data pipelines.

This is not a traditional reporting role. It is a role for someone who recognizes that the value chain of data is shifting from “pull a report” to “ensure the machine can interpret, validate, and surface insight autonomously.”

The specialist contributes to ensuring that data is structured, documented, governed, and contextually enriched so that both BI dashboards and AI products can deliver trusted and actionable outputs. The individual in this role is developing the ability to move fluidly between resolving a data quality issue, monitoring a vendor delivery, supporting a Power BI report, or preparing data for AI use cases — while continuously building the business understanding needed to appreciate why each task matters commercially.

This role operates with an AI-aware mindset. Tasks — from data validation to documentation — are performed with growing awareness of how they enable or constrain downstream AI capabilities. The specialist learns that clean, well-structured, and semantically rich data is foundational to AI-powered products and begins to shape their work accordingly to support AI readiness.

This means developing the habit of thinking beyond “is this data correct?” toward “can a machine interpret this data accurately and consistently?”

As organizations move from manual, request-driven analytics toward self-service and AI-augmented intelligence, this role contributes to the operational backbone that enables that transition — supporting data feeds, taxonomy updates, remediation workflows, and AI-ready datasets under the guidance of senior team members.

Key Tasks / What You’ll Do

• Support the coordination and monitoring of data deliveries from self-service analytics (SSA) platforms and external vendors, checking timeliness, completeness, and format compliance, and escalating issues or anomalies to senior team members as needed.
• Maintain and update business rules, mapping logic, taxonomies, and classification standards under guidance, ensuring they reflect current business and market realities and are structured for both human and machine consumption.
• Investigate and help resolve data quality issues by supporting root cause analysis, implementing corrective actions, and documenting resolutions for future prevention.
• Support analytics and BI reporting requests by preparing data, validating outputs, and helping maintain reports and dashboards, including Power BI deliverables.
• Help ensure reporting outputs are accurate, timely, and contextually relevant to business needs.
• Contribute to the documentation of data processes, business rules, issue resolutions, and data structures to improve transparency, repeatability, and governance.
• Assist in preparing and organizing data assets so they are usable across reporting, operational, and emerging AI-enabled use cases.
• Apply an AI-aware approach to operational work by considering how data quality, structure, and documentation affect machine interpretability and downstream automation.
• Collaborate with internal stakeholders, senior team members, and external data providers to support issue resolution, clarify requirements, and improve data reliability.
• Build commercial understanding and business context over time to better interpret data and support more meaningful insights and decision-making.

Role Profile

This role is suited for a professional who is:

• detail-oriented and execution-focused
• comfortable working with data operations and reporting support
• interested in building experience across data quality, taxonomies, mappings, and business rules
• motivated to develop capability in AI readiness and AI-enabled ways of working
• eager to combine technical learning with growing business and commercial understanding

The role requires someone who can operate effectively in a hands-on environment, learn quickly, and grow into broader ownership over time while supporting both current business reporting needs and future AI-enabled capabilities.