Senior BI Analyst

div]:bg-bg-000/50 [&_pre>div]:border-0.5 [&_pre>div]:border-border-400 [&_.ignore-pre-bg>div]:bg-transparent [&_.standard-markdown_:is(p,blockquote,h1,h2,h3,h4,h5,h6)]:pl-2 [&_.standard-markdown_:is(p,blockquote,ul,ol,h1,h2,h3,h4,h5,h6)]:pr-8 [&_.progressive-markdown_:is(p,blockquote,h1,h2,h3,h4,h5,h6)]:pl-2 [&_.progressive-markdown_:is(p,blockquote,ul,ol,h1,h2,h3,h4,h5,h6)]:pr-8"> _*]:min-w-0 gap-3 [&_>_*:last-child]:mb-0 print:block print:[&_>_*_+_*]:mt-3 standard-markdown"> Brainlabs is the independent, founder-led agency building the future of media. We have over 1000 Brainlabbers based across the global, all united through the 12 principles laid out in our Culture Code. We're full-service, with people and AI agents working side by side, all aligned to one thing: maximizing our clients' revenue through a genuinely scientific approach to media. If you want to help play your part in achieving this for the world's biggest brands in an environment that will support and challenge you in equal measure, this is where you do it.

The Senior BI Analyst will be responsible for leading BI initiatives, ensuring governance, and driving advanced analytics strategies. This role requires expertise in data visualization, automation, stakeholder management, and people leadership. The candidate is expected to oversee BI projects, manage reporting frameworks, implement governance processes, mentor teams, and enhance business impact through data-driven decision-making. AI is front and center in this role: the successful candidate will use AI-native BI tooling, connect dashboards directly to the data engineering team’s AI and GenAI pipeline outputs, implement automated anomaly detection, and enable prompt-driven self-service reporting so views update at pace without manual intervention.

What you do

BI Strategy and Governance:

• Define and implement BI strategy to align with business objectives.
• Establish governance frameworks for data integrity, security, and standardization.
• Develop and enforce best practices for data visualization, automation, and self-service reporting.
• Ensure compliance with data policies and regulatory requirements.

Advanced BI Platform and Dashboard Management:

• Oversee the development and optimization of dashboards using Datorama, Looker Studio, Tableau, or Power BI.
• Lead initiatives to automate reporting processes and improve data efficiency.
• Standardize reporting templates to drive consistency and accuracy across business units.
• Evaluate emerging BI tools and technologies for continuous improvements.
• Deploy AI-native BI features (e.g., Looker AI / Gemini integration, Tableau Pulse, or Copilot in Power BI) to automate dashboard generation, view refresh, and standardized reporting aligned with the data engineering team.
• Connect BI views directly to the data engineering team’s AI and GenAI pipeline outputs so dashboards reflect AI-generated data automatically,

• Develop detailed project plans with accurate time, resource, and effort estimates to ensure smooth project execution.
• Collaborate with internal teams to drive efficient project execution and maintain delivery standards.
• Address client and stakeholder escalations promptly, ensuring a structured resolution approach.
• Collaborate with senior leadership to design strategies that contribute to revenue growth and operational efficiency.

Data Governance and Quality Assurance:

• Define and monitor key data quality metrics across multiple data sources.
• Implement data validation frameworks to prevent inconsistencies and anomalies.
• Collaborate with data engineers to enhance data pipelines and ensure scalability.
• Drive initiatives to improve ETL processes and reduce data latency.

People Management and Team Development:

• Lead, mentor, and develop a team of BI specialists and analysts.
• Foster a culture of continuous learning and innovation within the BI team.
• Conduct performance evaluations, provide feedback, and identify training needs.
• Ensure effective collaboration within cross-functional teams to drive efficiency.

Process Optimization and Automation:

• Identify inefficiencies in reporting workflows and implement automation solutions.
• Drive the adoption of self-service BI tools to reduce manual reporting dependencies.
• Implement AI and ML capabilities across BI reporting, including predictive analytics, anomaly detection, and AI-generated narrative summaries that surface key data changes without manual effort.
• Enable prompt-driven, natural language querying of dashboards (e.g., via Gemini in Looker or Microsoft Copilot) so stakeholders get instant answers without raising manual reporting requests.
• Build and maintain standard BI views that connect directly to the data engineering team’s AI and GenAI pipeline outputs, ensuring dashboards reflect AI-generated data automatically and consistently across teams.
• Develop and maintain documentation for BI solutions, ensuring knowledge retention.
• Align BI initiatives with overall business goals and key performance indicators.

• Drive collaboration between data analysts, engineers, and business users to optimize insights delivery.
• Lead workshops and training sessions to enhance data literacy across teams. </ul&