Data Analyst

Senior / Advanced Data Operations Analyst

(Customer Service / Analytics Operations)

The Data Operations Analyst supports analytics and data processing operations by monitoring workflows, producing operational reports, and ensuring timely, accurate delivery of data-driven outputs. This role partners closely with analytics, data delivery, and leadership teams to provide visibility into performance metrics, volumes, and service levels.

The position requires strong analytical thinking, clear communication skills, and working familiarity with business intelligence and data tools.

• Prepare, validate, and distribute recurring operational and performance reports (e.g., cycle times, volumes, SLA metrics).
• Monitor data processing activities to identify delays, data quality issues, or anomalies and coordinate resolution with cross‑functional teams.
• Support service level tracking and performance management initiatives through metric analysis and reporting.
• Collaborate with analytics, data engineering, and operations teams to ensure consistent, accurate data outputs.
• Communicate status updates, trends, and risks to stakeholders in a clear and concise manner.
• Maintain documentation and standardized reporting processes to support operational efficiency and auditability.

• Experience in an analytics, data operations, customer service analytics, or performance management role.
• Strong attention to detail with the ability to interpret and validate data outputs.
• Proven ability to communicate data findings to both technical and non‑technical audiences.
• Experience working in cross‑functional, matrixed environments.

• Analytical and problem‑solving skills
• Data accuracy and quality awareness
• Process orientation and operational discipline
• Clear written and verbal communication
• Collaboration and stakeholder engagement

• Working familiarity with Power BI
  , including reviewing dashboards, validating metrics, and understanding visualizations.
• Basic to intermediate familiarity with SQL Server
  , such as reading queries, validating results, or performing simple data checks.
• Understanding of data pipelines, reporting workflows, or operational metrics.
• Experience supporting SLA, KPI, or performance reporting.

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Note:

Deep development expertise is not required; emphasis is on interpretation, validation, and operational use of data.)