Senior Data Analyst

Role Overview

Analytical Data Models

• Design and maintain dimensional models and semantic layers in Power BI or equivalent tools.
• Apply star schema, SCD and medallion-layer conventions and resolve modelling and performance bottlenecks.
• Define and document metrics and KPIs, including calculation logic, grain and refresh cadence.

Operational Analysis

• Investigate telemetry, crash logs, support records, incident data and observability signals across products and systems.
• Use complex SQL, Python and KQL queries to extract, join and analyse data from heterogeneous sources.
• Apply anomaly detection, trend analysis, cohort analysis and time-series methods to product quality signals.
• Support root-cause investigations with data-driven findings and recommendations.

BI Delivery

• Build and publish maintainable Power BI reports and dashboards using deployment, certification and version-control practices.
• Optimise DAX measures, report queries and visual-level query performance.
• Maintain documentation for measures, report logic and data sources.
• Partner with Data Engineering on pipeline validation, schema design and analytical data requirements.

Collaboration

• Work with Incident Management, Support, SRE Engineers, Software Development and Data Engineering teams.
• Communicate findings clearly to engineers, domain experts, project managers and business stakeholders.
• Help align data usage and retention practices with legal and compliance requirements, including GDPR.

Experience and Education

• Five to eight years of experience in a data-focused role such as Data Analyst, BI Developer or Analytics Engineer.
• BE or B.Tech degree in Computer Science, Software Engineering, Data Science or a related field.
• Production experience with analytical data models, multiple data sources and defined metrics frameworks.

Technical Skills

• Strong SQL skills, including window functions, CTEs, query optimisation and large datasets.
• Python proficiency for analytical work using pandas, NumPy and visualisation libraries.
• Power BI experience including DAX, semantic models, performance tuning and deployment.
• KQL proficiency for Azure Monitor, Log Analytics and Application Insights.
• Understanding of statistical analysis, data privacy and GDPR principles.
• Familiarity with Databricks, Azure data services and OpenTelemetry is preferred.

Personal Competencies

• Analytically rigorous, verifying data and findings before presenting them.
• Able to own work end-to-end, identify improvements and follow through on delivery.
• Communicates clearly with technical and non-technical audiences and structures ambiguous problems into analytical approaches.

About WSA