Senior Data & Analytics Specialist

Senior Data & Analytics Specialist

Major Tasks Purpose

The Senior Data & Analytics Specialist is a versatile, execution-oriented role positioned at the intersection of data operations, business intelligence, and AI enablement. This role represents the evolution of the traditional business data analyst: less focused on building static reports, and more focused on ensuring that data flows, data quality, and data structures are robust enough to support both human decision-making and AI-driven intelligence at scale.

The role combines hands-on data execution — including support for analytics requests, maintenance of business rules, issue troubleshooting, and coordination of vendor and platform data feeds — with a forward-looking responsibility to ensure data is AI-ready, to leverage AI tools in day-to-day operations, and to support the operationalization of AI use cases.

The specialist brings strong business context and commercial understanding, while also demonstrating the technical fluency required to work across platforms, taxonomies, and data pipelines. This is not a traditional reporting role. It is a role for someone who understands that the value chain of data is shifting from “pull a report” to “ensure the machine can interpret, validate, and surface insight autonomously.”

This role ensures that data is structured, documented, governed, and contextually enriched so that both BI dashboards and AI-powered products can generate trusted, relevant, and actionable outputs. The person in this position is equally comfortable resolving a data quality issue, coordinating a vendor delivery, enabling a Power BI report, or preparing data for AI consumption — and understands the commercial impact of each activity.

Critically, the role operates with an AI-first mindset. Every task — from data validation and mapping logic definition to taxonomy management and documentation — is executed with awareness of how it enables or constrains downstream AI capabilities. The specialist recognizes that clean, well-structured, and semantically rich data is foundational to AI-powered products and actively shapes their work to maximize AI readiness.

This means thinking beyond “is this data correct?” to also ask “can a machine interpret this data accurately, consistently, and at scale?”

As organizations move from manual, request-driven analytics toward self-service and AI-augmented intelligence, this role serves as a critical operational backbone that enables that transition — one data feed, one taxonomy update, one remediation workflow, and one AI-ready dataset at a time.

Key Tasks / What You’ll Do

• Coordinate and manage data deliveries from self-service analytics (SSA) platforms and external vendors, ensuring timeliness, completeness, and format compliance.
• Monitor incoming data feeds proactively to identify gaps, anomalies, inconsistencies, or structural drift before they create downstream impact.
• Maintain and update business rules, mapping logic, taxonomies, and classification standards, ensuring they reflect current business and market realities and are structured for both human and machine consumption.
• Troubleshoot data issues end-to-end, from issue detection through root cause analysis and corrective action, ensuring timely remediation and documenting resolutions to prevent recurrence.
• Support analytics and BI reporting needs by preparing data, validating outputs, maintaining Power BI dashboards, and ensuring reports reflect accurate, timely, and contextually correct business information.
• Provide support for local market data requests and other ad hoc analytical or operational data needs within the defined scope of the role.
• Ensure that data assets are properly documented, governed, and structured to improve usability, transparency, and trust across reporting and AI use cases.
• Apply an AI-first lens to daily work by identifying opportunities to improve data usability for machine interpretation, automation, and AI product integration.
• Contribute to the preparation and operational readiness of datasets used in AI-driven use cases, ensuring that data quality, consistency, and semantic clarity meet required standards.
• Collaborate with internal stakeholders, cross-functional teams, and external data providers to resolve issues, clarify requirements, and improve overall data reliability and usability.
• Use business understanding and commercial context to interpret data appropriately and ensure outputs are meaningful, actionable, and aligned with decision-making needs.

Role Profile

This role is suited for a professional who combines:

• strong execution discipline in data operations
• solid experience in analytics and BI support
• the ability to work across data structures, mappings, and taxonomies
• a practical understanding of AI/data readiness
• and the commercial acumen to connect data activities to business value

The role requires someone who is comfortable operating across both operational detail and strategic direction, helping bridge today’s reporting and data support needs with tomorrow’s AI-enabled business capabilities.