Overview

Lead Data Analyst (Data & Analytics) Key Responsibilities Team Leadership & CoordinationLead and coordinate the activities of the DataOps analyst team, ensuring clear ownership, accountability, and coverage.Establish and run effective triage processes for incoming data issues, incidents, and requests.Ensure analysts are working on the right problems at the right time, balancing

Responsibilities

• Team Leadership & Coordination
• Lead and coordinate the activities of the DataOps analyst team, ensuring clear ownership, accountability, and coverage.Establish and run effective triage processes for incoming data issues, incidents, and requests.
• Ensure analysts are working on the right problems at the right time, balancing urgent support needs with longer-term data projects.
• Provide coaching, feedback, and mentorship to analysts, supporting both technical growth and operational judgement.Become a recognized SME s core data flowsTriage, Workflow & Prioritisation
• Define, implement, and continuously refine workflows for:issue intake and triageInvestigation and resolutionEscalation to Data Engineering or other teamsCommunication and closure
• Act as the primary point of coordination for high-severity or cross-team data issues.
• Ensure priorities are clearly understood and agreed with stakeholders, and that trade-offs are made explicitly.Operational Effectiveness & Service QualityMonitor team effectiveness using qualitative and quantitative signals (e.g. response times, backlog health, recurring issues).Identify bottlenecks, failure modes, and areas of operational risk within the data support process.
• Drive initiatives to improve reliability, transparency, and predictability of DataOps outcomes.
• Ensure documentation, runbooks, and knowledge sharing are maintained and actively used.Stakeholder & Partner ManagementPartner closely with Customer Experience, Customer
• Support, Product, Partnerships, and Data Engineering to align expectations and delivery.
• Provide clear, timely communication to stakeholders on issue status, risks, and timelines.Represent DataOps in cross-functional discussions about data quality, supportability, and operational readiness.Tooling & Continuous Improvement
• Ensure the team effectively uses existing tooling, dashboards, and workflows to deliver data support.Identify gaps in tooling or process and drive the creation of new lightweight tools, metrics, or workflows where appropriate.