Revenue Intelligence Operations Analyst, Marketing
New
V
Veeam SoftwareData and AI Trust
Remote, United States, Central or Eastern Time ZoneFull-TimeEntry
SalaryZone 1: $73,500 - $122,400; Zone 2: $67,400 - $112,300; Zone 3: $61,200 - $102,000; Zone 4: $53,300 - $88,800 USD
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Job Details
- Required Skills
- PythonSQLData AnalysisGitMicrosoft Power BISalesforceGoogle AnalyticsTableauSparkDatabricks
Requirements
- Bachelor’s degree in Data Analytics, Computer Science, Statistics, Business Analytics, Marketing Analytics, or related quantitative field.
- 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).
- Exposure to Databricks, Apache Spark, or cloud-based data environments.
- Experience working with real-world datasets and performing data validation and troubleshooting.
- 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.
- Internship, academic project, or research experience involving data analysis is strongly preferred.
- Must reside in Central or Eastern Time Zone.
Responsibilities
- 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 to build interfaces, agents, and workflow automations.
- Develop and maintain dashboards and marketing performance reports using BI tools.
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