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Manager, Data Visualization

Job in New York, New York County, New York, 10261, USA
Listing for: Brain Labs Digital LTD.
Full Time position
Listed on 2026-06-06
Job specializations:
  • IT/Tech
    Data Analyst, Data Science Manager
Salary/Wage Range or Industry Benchmark: 80000 - 100000 USD Yearly USD 80000.00 100000.00 YEAR
Job Description & How to Apply Below
Position: Manager, Data Visualization New
Location: New York

Brainlabs is the media agency built to answer one question: what's actually driving profit? Founded in 2012 by Daniel Gilbert, we were built by engineers before we were a media agency. Today, 1,000+ Brainlabbers across five continents use our proprietary agents, built on 32 media tools and over 2,500 logged experiments, to help brands connect every channel they plan and buy to one thing: the bottom line.

Classification:
Full-time
Reporting to:
Director, Data Science

Location:

New York City, New York | Dallas, Texas | Boca Raton, Florida | San Francisco, California | Los Angeles, California
Compensation:
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.
Work Authorization:
Must be legally entitled to work in the United States

What's the role

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.

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…
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