Gerente de Dados & IA - Revenue Operations
Blip · São Paulo, São Paulo, Brazil
- On site
- Full-time
- $130,000 / year
- São Paulo, São Paulo, Brazil
Job highlights
- Lead data and AI for revenue operations.
- Transform data into actionable business decisions.
- Drive AI adoption across GTM teams.
- Enhance analytical maturity and automation.
- Manage multidisciplinary data teams.
About the role
Data & AI Manager - Revenue Operations
We are looking for a leader for the Data & Artificial Intelligence front within Revenue Operations, responsible for transforming data into decisions and leading the practical adoption of AI in Marketing, Sales, Partnerships, and Customer Success. This person will be key in evolving the company's analytical maturity—moving from reporting to decision intelligence and AI-driven automation.
Key Responsibilities
- Data Strategy for RevOps: Define and lead the data strategy for the entire revenue funnel (MKT, Sales, Partnerships, CS). Structure the unified data model (single source of truth). Ensure data consistency, quality, and governance. Evolve the company from descriptive dashboards to predictive and prescriptive analytics.
- Analytics & Insights Leadership: Build and scale a data area within RevOps (BI, Analytics, Data Ops). Define and track revenue performance KPIs (pipeline, conversion, churn, LTV, CAC, etc.). Generate actionable insights for executive leadership (CRO, VP Sales, Marketing, CS). Lead data and intelligence routines for forecasting, pipeline reviews, and performance analysis.
- AI Adoption in Go-to-Market: Lead the AI roadmap applied to Revenue (e.g., scoring, lead prioritization, churn prediction, next best action recommendation). Identify and implement high-impact use cases with generative and predictive AI. Act as a bridge between business and technical teams (Data Science/Engineering/Product). Ensure practical adoption of AI solutions (not just POCs). Reduce manual effort and increase GTM team productivity.
- Governance & Data Culture: Define data governance standards. Promote a data-driven culture throughout the organization. Enable stakeholders (trainings, playbooks, decision frameworks).
Candidate Profile
- Data & Analytics Experience: Solid experience with Data Modeling (Data Warehouse, ETL/ELT), BI Tools (e.g., Tableau, Power BI, Looker), and advanced SQL. Experience with SaaS/Revenue metrics: Pipeline, conversion, CAC, LTV, churn, NRR, forecast.
- AI & Advanced Analytics Experience: Practical experience with AI applications: Predictive models (forecast, churn, scoring), Generative AI applied to business. Familiarity with modern data stacks: CDP, Data Lake, ML/AI tools. Ability to translate business problems into analytical solutions.
- RevOps / GTM Experience: Experience with Sales processes (pipeline, forecast, territory planning), Marketing processes (lead generation, attribution), and Customer Success processes (retention, expansion). Experience with CRM (e.g., Salesforce) and ecosystem tools.
- Management Experience: Experience leading multidisciplinary teams (BI, Analytics, Data Ops). Experience in high-growth environments (scale-up or big tech).
Key Attributes
- Ownership Mentality: This person doesn't just 'deliver dashboards'—they solve business problems.
- Business-Technical Translation: Can converse with a CRO and a Data Scientist at the same level.
- Influence Without Authority: Will need to drive AI adoption in areas that do not report to them.
- Impact-Oriented Pragmatism: Focus on solutions that deliver results—not on unnecessary technical complexity.
- Data Storytelling: Ability to transform analyses into clear, actionable narratives.
- Change Management: Lead cultural transformation (data-driven + AI-driven). Handle resistance to change (especially in Sales).
Differentiators (Nice to Have)
- Previous experience scaling AI initiatives.
- Background in Data Science or Data Engineering.
- Experience in B2B SaaS companies.
- Familiarity with RevOps and modern GTM frameworks.
- Knowledge of automation and no-code/low-code tools.
Measuring Success
- Increased revenue predictability (forecast accuracy).
- Improved funnel efficiency (conversion, sales cycle).
- Reduced churn and increased expansion.
- Real adoption of AI solutions by GTM teams.
- Reduction of manual activities via automation.
- Data-driven maturity level of the organization.
Perks and Benefits
- Flexible Hours: More autonomy to organize your routine with balance and responsibility.
- Flexible Work Models: Remote, hybrid, or on-site, depending on the role's needs.
- No Dress Code: Freedom to be yourself, without formalities.
- Birthday Day Off: A day off in your birthday month to celebrate as you wish.
- Blip Recharge: 5 paid days off per year for roles without time tracking, to balance your workload.
- Meal/Food Voucher: R$ 1144.00 monthly, no deductions, credited during holidays and leave.
- Transportation Voucher: Available as needed for commuting.
- Wellhub (Gympass): Access to gyms, wellness apps, and physical activities, also for dependents.
- SESC Agreement: Access to culture, leisure, sports, hotels, vacation resorts, and more.
- Health Plan (Sulamérica): National coverage, private room for you and dependents, with only co-payment deducted.
- Dental Plan: National coverage for you and dependents, with three plan options, and full deduction of the chosen plan's cost.
- Conexa Saúde: Online psychological support platform.
- Life Insurance: Coverage equivalent to 24 times your monthly salary.
- Extended Maternity Leave: 180 days to enjoy this new phase.
- Extended Paternity Leave: 30 days to be present and strengthen bonds.
- Childcare Assistance: Reimbursement of R$ 676.81 for children up to 2 years and R$ 592.21 for children up to 5 years.
- Assistance for Dependents with Disabilities: Support of R$ 846.02 for children with disabilities or neurodiversity.
Key skills/competency
- Data Strategy
- Revenue Operations
- AI Adoption
- Predictive Analytics
- Data Modeling
- BI Tools
- SQL
- SaaS Metrics
- Change Management
- Leadership
Skills & topics
- Data Management
- Artificial Intelligence
- Revenue Operations
- Data Strategy
- Business Intelligence
- Predictive Analytics
- SaaS Metrics
- Machine Learning
- Data Modeling
- Leadership
- SQL
- Tableau
- Power BI
- Looker
- Salesforce
- Go-to-Market
- Scale-up
- Big Tech
- Change Management
- Data Governance
How to get hired
- Tailor your resume: Highlight experience in data modeling, BI tools, advanced SQL, SaaS metrics, and AI applications. Showcase your RevOps/GTM process knowledge and CRM expertise.
- Craft a compelling cover letter: Emphasize your ownership mentality, ability to translate business needs into analytical solutions, and experience in change management.
- Prepare for interviews: Be ready to discuss your experience leading teams, driving AI adoption, and influencing stakeholders. Prepare examples of how you've solved business problems with data.
- Showcase your impact: Quantify your achievements, particularly in improving forecast accuracy, funnel efficiency, and reducing manual tasks through AI and automation.
Technical preparation
Master advanced SQL for complex queries.,Practice data modeling concepts (DWH, ETL/ELT).,Build dashboards in Tableau, Power BI, or Looker.,Develop predictive models for forecasting/scoring.
Behavioral questions
Describe a time you influenced without authority.,How have you translated business problems to data solutions?,Share an experience leading change management initiatives.,How do you ensure data-driven decisions in teams?
Frequently asked questions
- What is the primary focus of the Data & AI Manager role at Blip?
- The primary focus of the Data & AI Manager for Revenue Operations at Blip is to leverage data and AI to drive strategic decision-making across Marketing, Sales, Partnerships, and Customer Success, enhancing the company's analytical maturity and automating processes.
- What kind of data and AI experience is required for this Blip job?
- The role requires solid experience in data modeling, BI tools, advanced SQL, and SaaS revenue metrics. Practical experience with predictive and generative AI applications, along with familiarity with modern data stacks, is also essential.
- What does Blip mean by 'Revenue Operations' in this role?
- Revenue Operations at Blip encompasses the entire revenue funnel, including Marketing, Sales, Partnerships, and Customer Success. The Data & AI Manager will align data strategy and AI initiatives across these departments to optimize revenue generation and customer lifecycle management.
- How does Blip approach AI adoption in its Go-to-Market strategy?
- Blip prioritizes the practical adoption of AI solutions within its Go-to-Market teams, focusing on identifying high-impact use cases like lead scoring, churn prediction, and next best action recommendations to reduce manual effort and boost productivity.
- What is expected in terms of data governance and culture at Blip?
- The Data & AI Manager is expected to define data governance standards and promote a data-driven culture throughout the organization. This includes empowering stakeholders with training, playbooks, and decision frameworks to ensure widespread data literacy and adoption.
- What are the key benefits of working at Blip in this Data & AI Manager role?
- Blip offers flexible work arrangements (remote, hybrid, on-site), flexible hours, a no dress code policy, and a comprehensive benefits package including meal vouchers, health and dental plans, life insurance, and extended parental leave.
- How does Blip measure success for the Data & AI Manager position?
- Success is measured by improvements in revenue predictability (forecast accuracy), funnel efficiency (conversion rates, sales cycle), churn reduction, expansion growth, actual AI solution adoption by GTM teams, and the overall data-driven maturity of the organization.