Service Desk Lead

Must Haves:

• 5 years in Service Desk
• 2 years of experience in a lead role (queue ownership, triage, and stakeholder management).
• Demonstrated experience building or operating an SLA-based support model (severity definitions, escalation paths, reporting, and continual improvement).
• Strong incident and problem management experience, including RCA facilitation and follow-through on corrective actions.
• Working knowledge of analytics/reporting environments (e.g., BI tools, semantic layers, data pipelines/ETL concepts) and common failure modes (data freshness, job failures, access issues).
• Ability to communicate clearly with both technical teams and business/client-facing stakeholders, including executive-ready status updates.
• Comfort with support tooling (ticketing system, knowledge base, dashboards); ability to define workflow rules and governance routines.
• Strong experience working with Tableau

Plus:

• ITIL Foundation (or equivalent service management training/experience).
• Experience supporting BI platforms such as ThoughtSpot and/or Tableau; familiarity with analytics migrations is a plus.
• SQL proficiency and ability to troubleshoot data quality issues across source-to-report pipelines.
• Experience implementing proactive monitoring/alerting (e.g., job/pipeline monitoring, synthetic checks, data freshness thresholds).
• Experience coordinating onshore/offshore delivery and follow-the-sun support models.

Day to Day

Own the day-to-day operation and continuous improvement of the Reporting & Analytics (R&A) Service Desk. This role establishes a dedicated, metric-driven support model that separates production support from development work, ensures reliable intake/triage/prioritization, delivers consistent SLA-based service to internal and client-facing users, and drives stability through root-cause analysis (RCA), proactive monitoring, and strong governance.

Key Responsibilities

1) Scope & Coverage (Support vs. Development)

• Define and maintain the R&A support service catalog (what the Service Desk owns vs. what is routed to development/product teams).
• Establish and enforce operating procedures that protect development capacity (clear intake criteria, escalation triggers, and handoffs).
• Own triage standards for reporting incidents, data issues, access requests, and “how-to” questions; ensure fast user response for straightforward issues.
• Coordinate flex capacity for surges (releases, migrations, systemic defects), including readiness plans, cross-training, and on-call/after-hours coverage where required.

2) SLA Model & Service Performance

• Define severity tiers and SLAs (response, restore/workaround, resolution) and ensure consistent interpretation across all support resources.
• Implement measurement, dashboards, and regular reporting of ticket volume, backlog, SLA attainment, aging, customer satisfaction, and recurring-issue trends.
• Run daily/weekly service management routines to prevent SLA breaches (queue hygiene, aging controls, clear prioritization, and escalations).
• Coordinate onshore/offshore workflows to ensure seamless handoffs and consistent service levels.

3) Operating Model & Governance

• Own end-to-end intake, triage, and prioritization so urgent work is handled quickly without allowing “everything is critical.”
• Serve as the single-threaded owner for the support queue: assign work, manage workload/capacity, and maintain clear accountability.
• Operate escalation paths and stakeholder communications for major incidents and customer-impacting issues.
• Lead governance cadences and artifacts (e.g., weekly service review, SLA/KPI dashboard, monthly trend and risk review, release/migration readiness support plan).

4) Stabilization, RCA, and Risk Reduction

• Drive problem management: identify recurring defects, lead RCA, document corrective/preventive actions, and track completion.
• Partner with engineering/data teams to turn high-frequency issues into durable fixes; maintain a prioritized “defect reduction” backlog.
• Implement and improve proactive monitoring for data freshness, job failures, pipeline/ETL health, and report availability; ensure alerting routes to the right responder.
• Demonstrate reduction in firefighting over time through trend metrics (repeat incidents, mean time to restore, backlog aging, and incident-to-problem conversion rate).

5) Transition, Knowledge, and Cost Predictability

• Lead transition from the current blended model to stabilized operations: discovery, onboarding, tooling alignment, and phased cutover with minimal disruption.
• Build and maintain knowledge assets (runbooks, SOPs, known error database, troubleshooting guides, and stakeholder-facing FAQs).
• Reduce key-person risk through documentation standards, cross-training, and role-based access management.
• Provide inputs to staffing/capacity planning and cost predictability (forecast volume, skill mix, and surge needs; track demand drivers)