Client Facing Data Analyst

Position Overview

As a Client Facing Data Analyst, you will play a crucial role in enabling data-driven decision-making by transforming, analyzing, and reporting with a variety of data across performance, commercial and operational systems. This role is ideal for a detail-oriented professional with a strong analytical mindset who thrives in a collaborative, data-rich environment.

Responsibilities

• Data Collection and Analysis
• Collect, analyze, and report data from various sources, ensuring comprehensive and accurate insights.
• Perform regular data quality checks to ensure accuracy and integrity across data sources.
• Identify trends, patterns, and anomalies in data to derive actionable insights that support strategic decision-making.
• Use natural language AI tools for ad hoc data exploration to accelerate discovery and guide areas of inquiry.
• Dashboard and Reporting Development
• Design, develop, and maintain dashboards and reports to monitor KPIs and other essential metrics.
• Present data findings and insights to clients and stakeholders in a clear, concise, and impactful manner.
• Create dashboard and reporting proofs of concept where appropriate with natural language AI tools (e.g. Google Gemini in Looker / Amazon Q in QuickSight).
• Client Engagement and KPI Development
• Guide clients in verbalizing their business goals and assist them in establishing KPIs to measure progress toward those goals.
• Proactively manage the iteration of these goals and metrics as you build trusted client relationships.
• Analytics Ownership and Insight
• Own analytics outputs end-to-end, from data validation and dashboard development through insight generation and stakeholder delivery.
• Take accountability for the accuracy, relevance, and adoption of analytics products, ensuring insights are clearly communicated and actionable for both client and internal stakeholders.
• Proactively identify opportunities to improve reporting, refine KPIs, and surface recommendations that support operational and strategic decision-making.
• Collaborate with engineering on cutting edge approaches to provide clients with access to agents trained on their data (Google BigQuery Agent Analytics, Amazon Redshift/Bedrock/Q, Azure Synapse/ML).
• Cross-Functional Collaboration
• Collaborate with cross-functional teams to identify data needs and provide analytical support aligned with project goals.
• Strategy and Process Improvement
• Contribute to the development and implementation of data-driven strategies and initiatives across multiple projects.
• Contribute to project improvement methodologies, benchmarking and change management practices to enhance project outcomes.

Knowledge, Skills & Experience

• 4–6 years of experience in a data analyst, business intelligence, or analytics-focused role with a strong track record in data analysis and reporting.
• Bachelor’s degree in Business, Data & Analytics, Information Systems, or a related field.
• Prior experience in sports, live events & entertainment, or consulting is preferred.
• Proficiency with data visualization tools such as Power BI, Tableau, or Looker, and strong SQL skills for data extraction, transformation, and analysis.
• Experience working with relational and analytical databases such as PostgreSQL, MySQL, BigQuery, Redshift, or Snowflake.
• Familiarity with cloud analytics platforms and tooling across AWS, Google Cloud Platform, or Azure.
• Ability to leverage AI-assisted analytics capabilities across cloud platforms for data preparation, validation, and analysis, with familiarity in AI-enabled SQL functions and emerging ML tools such as BigQuery ML, AWS SageMaker, or Azure Synapse/ML.
• Strong analytical and problem-solving skills with high attention to detail and the ability to manage multiple priorities.
• Exceptional verbal and written communication skills, with the ability to present insights to both technical and non-technical audiences.
• Demonstrated initiative, ownership, and accountability in delivering high-quality analytics work.
• Familiarity with data privacy and data governance practices is a plus.