Manager, Data Visualization

Brainlabs

10h • $50,000 - $105,000 • Onsite

About The Position

The Manager 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.

Requirements

• Bachelor's degree in Engineering, Computer Science, Business Analytics, Data Science, or a related field.
• 4-7 years of experience in BI, data analytics, or data visualization.
• Expertise in at least two BI tools: Datorama, Looker Studio, Tableau, or Power BI.
• Strong knowledge of SQL for querying and data manipulation.
• Excellent problem-solving skills with a strategic mindset.
• Experience in implementing data governance frameworks and best practices.
• Demonstrated experience using AI-native BI features (Looker AI, Tableau Pulse, or Copilot in Power BI) to build, automate, and refresh dashboards at pace without manual intervention.
• Proven ability to design and maintain BI views that integrate directly with AI/ML pipeline outputs from the data engineering team, including model-generated data and GenAI process results.
• Hands-on experience implementing automated anomaly detection and AI-generated narrative summaries within BI reporting environments.
• Must be legally entitled to work in the United States

Nice To Haves

• Certifications in BI tools such as Tableau, Power BI, or Looker.
• Experience in marketing analytics, media performance reporting, or digital advertising data.
• Familiarity with scripting languages like Python or R for data automation.
• Exposure to cloud-based data platforms like BigQuery, Snowflake, or AWS.
• Experience in Agile methodologies and project management frameworks.
• Knowledge of AI/ML techniques for predictive analytics.
• Familiarity with natural language query interfaces for BI (e.g., Gemini in Looker, Microsoft Copilot in Power BI, or Tableau Ask Data) and experience enabling prompt-driven self-service reporting for stakeholders.

Responsibilities

• 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.
• 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.
• 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.
• 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.
• 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.
• Manage multiple BI projects with competing priorities, ensuring timely delivery.
• Balance workload effectively while maintaining high-quality outputs.
• Implement project management best practices to improve reporting efficiency.
• Maintain clear and consistent communication with senior leadership regarding BI initiatives.
• Provide data-driven recommendations to support executive decision-making.

Benefits

• We are open to hiring candidates in our various office locations across the United States. We also receive applications from, and hire, candidates with varying levels of experience for example those who have a few years experience in a role to those who are looking to make a step up. The salary ranges on our job postings are set so as to account for these variable factors with decisions on the salary to be offered only made once we know the experience and location of our new hire.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level