Revenue Intelligence Operations Analyst, Veeam

• Strong working knowledge of SQL, including joins, aggregations, and data transformations
• Basic to intermediate proficiency in Python with experience using data libraries (e.g., pandas, NumPy) through coursework, projects, or internships
• Exposure to Databricks, Apache Spark, or cloud-based data environments
• Experience working with real-world datasets and performing data validation and troubleshooting
• Strong curiosity and willingness to learn
• Strong analytical and problem-solving abilities with attention to detail
• Ability to communicate technical findings to non-technical audiences
• Ability to manage multiple priorities and collaborate effectively across teams
• Bachelor’s degree in Data Analytics, Computer Science, Statistics, Business Analytics, Marketing Analytics, or related quantitative field
• Internship, academic project, or research experience involving data analysis is strongly preferred

Desirable

• This role offers the opportunity to work hands-on with large-scale marketing and customer datasets while building a strong foundation in data and marketing analytics
• You will receive mentorship and development in SQL, Python, Databricks, and modern analytics tools, while gaining exposure to cloud-based analytics and data engineering practices
• This is an excellent opportunity for an early-career analyst looking to develop technical expertise, AI fluency, and business acumen in a collaborative, data-driven environment
• Analyze marketing performance data to identify trends, performance drivers, and optimization opportunities
• Evaluate customer acquisition, engagement, and conversion metrics to support marketing decision-making
• Design and implement scalable lead ingestion solutions using AI-driven data parsing, validation, enrichment, and automation techniques
• Translate complex data into clear insights and recommendations for stakeholders
• Support ad-hoc analysis and proactively identify opportunities for deeper insights
• Write efficient SQL queries to extract, transform, and analyze marketing and enterprise data
• Use Python for data preparation, automation, and analysis
• Assist with building and maintaining curated datasets, data models, and data quality checks
• Utilize AI-assisted development tools, including Claude Code, to build interfaces, agents, and workflow automations
• Develop and maintain dashboards and marketing performance reports using BI tools
• Automate recurring reporting processes to improve efficiency and scalability
• Partner with marketing, analytics, data science and data engineering teams to support reporting and data needs
• Document data definitions, logic, and reporting methodologies