V
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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