About the role

Data Analytics role is part of the Digital Architecture & Solution Design team, supporting data readiness across BT’s digital platforms.

With strong experience in enterprise data environments, cross-functional collaboration, and data lifecycle management, you will contribute to ensuring that data is structured, reliable, and aligned with business needs. You bring the ability to work across multiple data domains and platforms, enabling seamless coordination between business, architecture, and engineering teams.

In addition, your ability to work across complex data landscapes and stakeholder groups helps drive consistency, improve data quality, and support scalable solutions. You contribute to building structured and well-governed data foundations that enable better insights and operational effectiveness.
Your experience supports BT’s transformation towards simplified, scalable, and AI-enabled digital ecosystems, with a focus on improving overall data usability and efficiency.

What you’ll be doing

• Supports the acquisition, processing, integration and quality assurance of data from multiple sources, including the design, coding, testing and deployment of data processes for ingestion, transformation or curation.
• Uses appropriate tools and techniques to automate data collection and build repeatable analytical outputs, reports and dashboards aligned to agreed business requirements.
• Undertakes initial data investigation and analysis to identify suitable data sources, validate data quality and surface trends or insight opportunities.
• Supports the development and refinement of commercial data products, analytical routines and self-serve reporting solutions that inform planning and decision making.
• Monitors and maintains key reporting metrics (e.g., revenue, consumption and other KPIs) to enable effective business performance tracking.
• Follows best practices, standards and Agile delivery approaches to ensure consistent, secure and high-quality outputs.
• Analyses business needs and works with stakeholders to shape data requirements and solution options, ensuring clarity, alignment and effective collaboration.
• Identifies and implements improvements to data analytics processes, driving efficiency, reliability and continuous improvement across the area.

Essential Skills / Experience

• Analyse and validate data requirements across systems.
• Review data structures, schemas, and metadata to support data readiness.
• Identify gaps and work with engineering teams to resolve data issues.
• Translate business needs into clear data mappings and documentation.
• Collaborate with architects, engineers, product, and cross-functional teams to ensure alignment across systems and business processes.
• Track data onboarding progress and highlight risks.
• Support compliance-related data validation and reporting.
• Document data flows, lineage, and definitions.
• Help build dashboards to monitor data quality and overall pipeline health.
• Support end-to-end data lifecycle activities, from requirement understanding to validation and documentation.
• Contribute to improving data quality, consistency, and standardisation practices.
• Participate in data architecture and design discussions, providing inputs on usability and scalability.
• Enhance process efficiency through improved documentation, tracking, and coordination.
• Identify opportunities for automation and optimisation in data-related workflows.

Desirable Skills / Experience

Essential:
• Strong SQL skills and comfort with large datasets.
• Understanding of ingestion pipelines, APIs and data platforms.
• Ability to interpret schemas, metadata and data models.
• Problem‑solving skills to identify root causes.
• Clear communication skills for technical and non‑technical audiences.
• Experience working with cross‑functional teams.
• Strong documentation skills (Markdown, Confluence, Excel).

Desirable:
• Experience with cloud data platforms.
• Knowledge of governance principles (lineage, ownership, quality).
• Exposure to compliance/regulatory data work.
• Familiarity with data contracts and event‑driven architecture.
• Experience building dashboards or trackers.
• Understanding of AI/ML concepts (pattern detection, classification).
• Experience using AI tools
• Ability to use AI for data validation, summarisation or accelerating documentation.