About the Role

We are looking for a Revenue Operations Analyst to join our Data Science & Analytics organization. This role is ideal for someone with a strong analytical foundation who thrives in understanding how operational work connects with analytics —understanding how data flows across systems, driving process improvements, and ensuring the integrity of revenue data across the business. 

A key focus of this role will be developing a deep understanding of Salesforce Revenue Lifecycle Management (RLM)—how it structures and surfaces revenue data, how it integrates with downstream systems, and what that means for our analytics and reporting. You’ll partner cross-functionally with Sales, Finance, IT, and other stakeholders to ensure data accuracy, consistency, and usability across the business. 

What You’ll Do

• Own and improve revenue data operations processes, with a focus on how data flows from and within Salesforce, RLM, and connected systems 

• Serve as a key contributor to the Salesforce RLM migration, helping define data mappings, validate data integrity, and support end-to-end testing 

• Partner cross-functionally with Sales Operations, Finance, IT, and Business Systems teams to align on data definitions, processes, and system requirements 

• Identify gaps, inefficiencies, and risks in current data workflows and propose scalable solutions 

• Write SQL queries to extract, validate, and analyze revenue data across multiple platforms 

• Build and maintain Tableau dashboards to support operational visibility and stakeholder reporting 

• Document data flows, business rules, and standard operating procedures related to revenue operations 

• Investigate key questions and requirements from leadership and problem solve with creative solutions  

. 

What You’ll Bring

• 3–7+ years of experience in revenue operations, data operations, business systems analysis, or a related analytical/operational role 

• Strong understanding of Salesforce, including data architecture, objects, and reporting 

• Experience with system migrations or large-scale data transformation projects 

• Proficiency in SQL for data extraction, validation, and analysis 

• An analytical mindset paired with a genuine interest in process design and operational excellence 

• Proven ability to work independently and cross-functionally, driving projects forward without needing to be directed step-by-step 

• Excellent communication skills—you can translate technical data concepts for non-technical stakeholders 

Bonus Skills

• Direct experience with Salesforce Revenue Lifecycle Management (RLM) 

• Experience building dashboards and visualizations in Tableau 

• Familiarity with subscription/SaaS revenue models (ARR, NRR, churn, upsell/downsell) 

• Background in data governance or data quality management 

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About the Role 

We’re looking for an ML/AI Ops Engineer with 7+ years of experience to own the end-to-end operationalization of our ML/AI solutions, ensuring models move smoothly from development to scalable, reliable production products. In this role, you’ll design and automate CI/CD pipelines, build and optimize model lifecycle workflows, monitor deployed models for performance, drift, and reliability, and integrate intelligence products into various digital tools such as Copilot, Salesforce, and Tableau. You’ll collaborate closely with Data Scientists, Data Engineers, and Data Architects to transform high-quality research models into robust, production-grade products. This is a key role in shaping a modern ML/AI lifecycle—from CI/CD to high governance. 

What You’ll Do 

• Own the end-to-end operationalization of ML and AI solutions—from development to scalable, reliable production systemsthat integrateseamlessly with other digital tools. 
  • Design, automate, and maintain CI/CD pipelines for model training, testing, deployment, and retraining (Azure DevOps, Databricks). 
  • Build, optimize, and version model lifecycle workflows, ensuring reproducibility, lineage, and governance across the ML/AI platform. 
  • Monitor production models for performance, drift, reliability, and resource usage; implement automated retraining workflows. 
  • Optimize compute, storage, and orchestration across the Databricks platform to ensure efficient, cost-effective operations. 
  • Collaborate closely with ML/AI Scientists, Data Engineers, and DWH team to transform research-grade models into production-ready services. 
  • Contribute to advancing our ML/AI platform, tooling, automation standards, and best practices. 

What You’ll Bring 

• Solid experience in operationalizing ML/AI models, including deployment, automation, monitoring, and lifecycle management.
• Strong programming skills in Python,PySpark, and SQL with clean, efficient, production-ready code.
• Experienced in feature engineering with a practical understanding of data engineering fundamentals - designing, validating, and optimizing feature pipelines, and ensuring feature consistency
• Experience in building Vector embeddings & RAG systems.
• Familiarity in ML and LLM models development and libraries used.
• Experience with MLflow (or similar tools) for model tracking, registry management, and lifecycle operations.
• Familiarity with CI/CD pipelines (Azure DevOps preferred)
• Strong grasp of data versioning, model versioning, reproducibility, and data lineage within governed ML/AI environments.
• Experience designing, consuming, or integrating REST APIs to expose ML/AI models as services and support real-time or near-real-time inference.
• Experience monitoring production models, identifying drift or performance issues, and implementing corrective workflows.
• A collaborative, systems-thinking mindset, working closely with ML/AI Scientists, Data Engineers, and Data Warehouse team. 

Bonus Skills 

• Understanding ofdata quality frameworks and how they integrate into ML pipelines.
• Comfort with infrastructure-as-code for provisioning and managing ML/AI platform components. 
• Working knowledge of Unix environments and general DevOps principles; exposure to Docker/Kubernetes is beneficial.
• Experience with real-time or near-real-time serving architectures, event-driven systems, or streaming-based inference.
• Experience with AI agent tools and MCP servers. 
• Strong interest in contributing to internal ML/AI platform evolution, including tooling, automation, standards, and best practices.

What You’ll Get 

• Two weeks of paid vacation, 12 statutory holidays, plus 4 extra global VeeaMe Days for self-care and 24 paid volunteer hours annually through Veeam Cares
• Paid parental leave: 8 days for fathers, 122 days for birthing parents, 92 days for adoptive parents
• Medical, dental, and vision coverage fully funded through INS Premium for employees and dependents
• Mental health support, therapy sessions, and virtual care via our Employee Assistance Program
• Retirement and social security contributions through Costa Rica’s statutory programs
• Life insurance equal to 24x monthly salary, plus disability and funeral coverage
• Daily cafeteria subsidy
• Fertility, adoption, and surrogacy support, plus 24 paid volunteer hours through Veeam Cares
• Opportunities to learn and grow through on-demand libraries (LinkedIn Learning, O’Reilly), mentoring, workshops, and learning events like our annual Global Day of Learning

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About the Role

We’re looking for a Data Science Engineer with 7+ years of experience to join the Revenue Intelligence team at Veeam. This role is ideal for someone who thrives in a fast-paced environment, enjoys building scalable data solutions, and is passionate about driving business impact through analytics, machine learning, and AI. You’ll work closely with cross-functional teams to turn data into actionable insights and intelligent applications.

What You’ll Do

• Design and implement data science, machine learning, and AI solutions to support strategic decision-making
• Perform deep-dive quantitative and qualitative analyses to validate business hypotheses and drive improvements
• Contribute to cross-functional initiatives involving data science, ML, and AI engineering use cases
• Develop knowledge bases from structured and unstructured data to support RAG systems and AI agents
• Build data-driven applications (e.g., Streamlit) to enable internal access to AI-powered capabilities
• Partner with stakeholders to deliver actionable insights and recommendations
• Continuously improve processes and identify opportunities for automation and efficiency

Technologies You’ll Work With

Python, SQL, Machine Learning & AI Frameworks, Databricks / PySpark, Data Visualization Tools (Streamlit, Tableau, Power BI, Qlik)

What You’ll Bring

• 7+ years of professional experience in data science, analytics, or machine learning roles
• Strong proficiency in Python and SQL
• Experience building scalable data science solutions (feature engineering, model training, evaluation, deployment, MLOps)
• English Bilingual
• Solid understanding of data engineering concepts (ETL/ELT, data modeling, pipelines, governance)
• Experience integrating LLMs into production systems (prompt engineering, RAG, AI agents)

Bonus Skills

• Experience with software engineering best practices (APIs, testing, version control, deployment)
• Hands-on experience with Databricks or PySpark
• Familiarity with data visualization platforms and storytelling with data
• Experience using project management and collaboration tools (Jira, Trello, Confluence)
• Strong technical writing and documentation skills

What You’ll Get

• Two weeks of paid vacation, 12 statutory holidays, plus 4 extra global VeeaMe Days for self-care and 24 paid volunteer hours annually through Veeam Cares
• Paid parental leave: 8 days for fathers, 122 days for birthing parents, 92 days for adoptive parents
• Medical, dental, and vision coverage fully funded through INS Premium for employees and dependents
• Mental health support, therapy sessions, and virtual care via our Employee Assistance Program
• Retirement and social security contributions through Costa Rica’s statutory programs
• Life insurance equal to 24x monthly salary, plus disability and funeral coverage
• Daily cafeteria subsidy
• Fertility, adoption, and surrogacy support, plus 24 paid volunteer hours through Veeam Cares
• Opportunities to learn and grow through on-demand libraries (LinkedIn Learning, O’Reilly), mentoring, workshops, and learning events like our annual Global Day of Learning

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About the Role

As the Director of Data Analytics focused on Annual Recurring Revenue (ARR), you will report directly to the Vice President of Data Science and Analytics. You will manage a team focused on leading the end-to-end development, operationalization, and enhancement of Veeam’s most critical corporate metrics, with ARR as your primary focus. You will drive the vision, strategy, and execution of data initiatives that fuel data-driven decision-making across all levels of the organization. 

This is a high-impact, visible role that requires a blend of technical expertise, strategic leadership, and business acumen. You will oversee a dedicated team, collaborating with stakeholders across Finance, Sales, HR, Product, and Engineering to architect scalable data solutions that deliver clear, actionable insights and support both internal and external reporting requirements. 

Critical thinking and problem solving, strong analytical business skills, SQL skills and experience with ARR are all critical components to success.  Strong management skills and excellent communication skills are also key. While ARR is the primary metric, the team is also involved in other strategic analytics projects, often in their incubation stage. 

What you'll do

Strategic Leadership & Roadmap Development 

• Define and execute the data analytics strategy and roadmap for Veeam’s Corporate Metrics, with an emphasis on ARR, in partnership with executive leadership and cross-functional stakeholders. 
• Set the vision for metric development, reporting standards, and analytics capabilities that drive organizational success. 

Metrics Design & Execution 

• Own the end-to-end process for defining, refining, and reporting on key performance indicators—including ARR, CAC, and other SaaS metrics.
• Build, maintain, and scale sustainable data assets and reporting frameworks to ensure accuracy, consistency, and compliance. 

Cross-Functional Collaboration 

• Lead and develop a high-performing team, fostering a culture of innovation, excellence, and accountability.
• Collaborate closely with Data Science, Analytics, Engineering, and Reporting teams to deliver business context, translate requirements, and co-create data solutions.
• Serve as a key partner in enterprise projects, such as CRM or Quote-to-Cash platform transformations, representing the needs of Corporate Metrics. 

Data Quality & Governance

• Champion data integrity, partnering with Data Governance and Quality teams to implement robust processes and standards for data accuracy and compliance. 

Change Management & Communication 

• Act as the primary liaison for data-driven initiatives, communicating complex data concepts to both technical and non-technical stakeholders.
• Drive process improvement, change management, and adoption of new analytics capabilities across the organization

What You’ll Bring

• 12+ years of experience in data analytics, data product development, or business intelligence, with significant time spent in SaaS or high-growth technology environments.
• 5+ years of experience leading and developing data teams.
• Bachelor’s or Master’s degree in Business Administration, Finance, Management, Information Systems, Computer Science, or related field (preferred).
• Expertise in Annual Recurring Revenue (ARR) and SaaS financial metrics.
• Proficiency in CRM and Quote-to-Cash systems, especially Salesforce.
• Advanced technical skills in SQL and experience with data warehousing and handling large datasets.
• Hands-on experience with business intelligence and analytics tools, especially Tableau  
• Conversational understanding of data architecture, engineering, and data science concepts.
• Demonstrated ability to develop and implement reporting strategies and processes for public companies.
• Excellent communication, leadership, and collaboration skills.
• Strong analytical thinking, problem-solving ability, and a passion for continuous improvement. 

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About the Role

We're looking for a Senior Data Analyst to own the delivery of corporate dashboards and analytical insights that drive strategic decision-making across Veeam. In this role, you'll be responsible for a broad portfolio of corporate metrics — with ARR and subscription revenue analytics as a primary focus — building, maintaining, and evolving the dashboards and reporting that senior leadership relies on to understand business performance. 

Reporting to the Director of Data Analytics, this is a high-visibility position. You'll work directly with VPs and C-level stakeholders to translate complex SaaS metrics into clear, actionable stories. If you thrive at the intersection of data, design, and business strategy, this role is for you. 

What You’ll Do

• Own the Corporate Dashboard Portfolio: Design, build, and maintain Tableau dashboards spanning key corporate metrics, with a primary focus on ARR, incremental ARR, net revenue retention (NRR), acquisition, upsell, downsell, and churn. 

• Deliver Analytical Insights: Go beyond reporting — proactively surface trends, anomalies, and opportunities across corporate and revenue data and present findings to senior leadership. 

• Partner with Stakeholders: Serve as the primary analytics point of contact for executive and cross-functional teams, translating business questions into data-driven answers. 

• Write and Optimize SQL: Query large-scale databases to extract, transform, and validate data for dashboards and ad hoc analyses. 

• Maintain Data Quality: Collaborate with data engineering to ensure upstream data pipelines produce accurate, timely inputs for reporting. 

• Drive Continuous Improvement: Identify opportunities to improve existing dashboards, automate manual reporting, and introduce new analytical capabilities — including AI-assisted tools where appropriate. 
• Document and Standardize: Establish clear definitions, data dictionaries, and best practices for corporate and ARR-related metrics across the organization. 

What You’ll Bring

• 5+ years of experience in a data analyst, business intelligence, or analytics engineering role, ideally within a SaaS or subscription-revenue environment. 

• Advanced SQL skills. You write efficient, well-structured queries and are comfortable working with large, complex datasets. Experience with modern cloud data platforms (e.g., Databricks, Snowflake, Redshift) is a strong plus. 

• Tableau expertise. You've built polished, production-grade dashboards from scratch — not just modified existing views. You understand calculated fields, LOD expressions, performance optimization, and publishing/governance workflows. 

• Executive communication skills. You're comfortable presenting to senior leaders, fielding tough questions, and distilling complex data into clear narratives. 

• Strong business acumen. You understand corporate performance metrics and SaaS fundamentals — ARR, MRR, NRR, churn, expansion, contraction — and how they connect to the broader business. 

• Self-directed and proactive. You take ownership of your domain, anticipate stakeholder needs, and don't wait to be told what to analyze.  Strong critical thinking and intellectual curiosity are key. 

Bonus Skills

• Experience with AI/ML tools and techniques applied to analytics workflows (e.g., automated anomaly detection, natural language insights generation, predictive modeling, or using LLMs to augment data analysis). 

• Familiarity with data modeling for subscription/recurring revenue businesses. 

• Experience with Python or R for statistical analysis, data wrangling, or automation. 

• Background working in a high-growth or enterprise software environment. 

• Exposure to data governance and catalog tools (e.g., Alation, dbt, or similar). 

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About the Role

At Veeam Software, we’re on a mission to become a truly AI‑powered organization, and trusted data is at the core of that transformation.

As the The Senior Director of AI‑Ready Data Governance owns the company‑wide mandate to ensure Veeam’s data is trusted, governed, and ready to power AI at scale. Building on core data management foundations, this role extends governance to AI agents, models, and sources of trust, ensuring AI products, insights, and decisions are safe, explainable, and reliable. Operating with visibility to the COO, CIO, and SVP leadership, this role ensures data governance is no longer a back‑office function, but a strategic enabler of Veeam’s ambition to become an AI‑powered company.

What You’ll Do

• Own and evolve enterprise data governance to ensure data is reliable, explainable, and fit for AI consumption, not just analytics or reporting
• Establish clear standards for data definitions, ownership, quality, lineage, and access across core domains (e.g., Account, Customer, Product, ARR, Employee)
• Define and enforce clear data quality thresholds required before data can be used by AI systems, including accuracy, completeness, timeliness, and consistency
• Create explicit “AI‑approved” vs. “not AI‑ready” data classifications to remove ambiguity for AI and internal AI product teams
• Certify authoritative datasets, metrics, and definitions that AI agents, models, and analytics must use. Actively reduce duplicate, unofficial, or unmanaged datasets that lead to conflicting answers, model drift, and loss of trust
• Extend data governance beyond tables and dashboards to AI agents, features, and models, ensuring clarity on what data they use, how it is transformed, and where accountability sits
• Maintain end‑to‑end data lineage from source systems through transformations to AI outputs
• Work closely with Data Science, AI, and Sales AI teams to embed governance into AI design and delivery, rather than bolting it on after the fact
• Serve as the primary data governance partner to Security, Legal, Privacy, and Risk, ensuring AI data usage aligns with regulatory, contractual, and customer commitments
• Treat AI data inputs as living assets, continuously monitoring for drift, degradation, misuse, or changing business context as AI adoption scales.

What You’ll Bring

• Proven experience leading enterprise data governance, data management, or data platform initiatives in a SaaS or enterprise environment
• Strong understanding of how data supports AI/ML systems and data‑driven decision making
• Experience building and scaling enterprise data governance frameworks
• Solid foundation in data quality, data lineage, and metadata management
• Ability to balance strategic vision with hands‑on execution
• Experience working cross‑functionally with both technical and business stakeholders
• Strong communication and leadership skills, with the ability to influence at all levels of the organization
• Bonus Skills
• Experience working on or supporting AI‑driven products or platforms
• Background in data architecture, data engineering, or analytics engineering
• Familiarity with AI governance, explainability, or responsible AI practices
• Experience in high‑growth SaaS or cloud environments
• Advanced degree in a relevant field