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Revenue Intelligence Operations Analyst (Marketing)

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Onsite

Revenue Intelligence Operations Analyst (Marketing)

Veeam

Revenue Intelligence Operations Analyst (Marketing)

Skills

SQL QueriesData EngineeringTableauPythonData ScienceNumPypandasDatabricksGitData AnalysisAISalesforceGoogle AnalyticsPower BI

2 months ago

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Important information


Contract type:

Permanent

Salary:

$53,300 – $122,400 / year

Location:

United States

Work mode:

Onsite

Published on:

12 August 2026

What they need


  • 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

Benefits

  • Unlimited paid time off, plus 3 global VeeaMe Days for self-care
  • Paid parental leave: 8 weeks for all parents, 16 weeks for birthing parents
  • Medical, dental, and vision coverage from day one
  • Mental health support, therapy sessions, and digital wellness tools via SupportLinc EAP
  • Fertility, adoption, and surrogacy support through Maven, plus paid volunteer time
  • 401(k) retirement plan with matching contributions up to annual limits
  • AirVet: 24/7 virtual veterinary care at no cost
  • Legal services, identity protection, and supplemental health insurance options
  • Professional training and education, including courses and workshops, internal meetups, and unlimited access to our online learning platforms (LinkedIn Learning, Athena, O’Reilly) and mentoring through our MentorLab program
  • Tax-advantaged spending accounts for healthcare, dependent care, and commuting- Strong working knowledge of SQL, including joins, aggregations, and data transformations
  • Experience working with real-world datasets and performing data validation and troubleshooting
  • 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
  • Bachelor’s degree in Data Analytics, Computer Science, Statistics, Business Analytics, Marketing Analytics, or related quantitative field
  • Strong analytical and problem-solving abilities with attention to detail
  • Ability to manage multiple priorities and collaborate effectively across teams
  • Ability to communicate technical findings to non-technical audiences
  • Strong curiosity and willingness to learn
  • Internship, academic project, or research experience involving data analysis is strongly preferred
  • Experience with Tableau, Power BI, or similar visualization tools
  • Exposure to marketing platforms such as Google Analytics or Salesforce
  • Familiarity with marketing analytics concepts or campaign performance metrics
  • Experience using version control tools (e.g., Git)
  • Understanding of ETL or data pipeline concepts

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