Marketing Data Engineering Intern at AvePoint in DC-Baltimore Area

Summary: AvePoint is seeking a Marketing Data Engineering Intern to support the launch of Campaign360, a strategic initiative aimed at unifying and standardizing marketing campaign data. The intern will work with modern data engineering tools to build a scalable data foundation and contribute to various data engineering tasks that enhance campaign performance reporting and analytics. Responsibilities: - Support discovery and data mapping efforts by identifying and documenting key marketing and customer data sources (e.g., CRM, marketing automation, web, product data) - Assist in designing and building ETL pipelines within Microsoft Fabric to ingest and transform marketing data into a Lakehouse environment - Develop and maintain curated datasets related to campaign performance, funnel stages, lead progression, and pipeline contribution - Help standardize campaign, lead, and opportunity data to improve data quality, consistency, and reporting reliability - Implement basic data quality checks, refresh schedules, and validation processes to ensure accuracy and completeness of datasets - Contribute to building an integrated Campaign360 data model that links campaigns to leads, opportunities, and pipeline - Support foundational attribution logic and prepare data for downstream analytics and dashboards - Partner with Marketing and Analytics teams to validate outputs, document metrics and data definitions, and support reporting enablement - Assist with documentation, knowledge transfer, and handoff materials to support long-term scalability Required Qualifications: - Currently pursuing a degree in Computer Science, Data Analytics, Information Systems, Engineering, or a related field (rising sophomore through graduate level) - Interest in data engineering, analytics, or marketing data ecosystems - Familiarity with SQL and data transformation concepts - Strong analytical and problem-solving skills with attention to detail - Ability to work with ambiguous data and evolving requirements - Clear communication skills and willingness to collaborate cross-functionally - Curiosity and eagerness to learn modern data engineering practices Preferred Qualifications: - Coursework or project experience in data engineering, distributed data processing, or analytics engineering is a plus - Experience With Python (pandas Or PySpark Preferred) - Exposure to ETL/ELT pipelines, data modeling, or Lakehouse/data warehouse concepts - Understanding of marketing or customer data is a plus - Experience or interest in Microsoft Fabric, Power BI, or similar platforms is preferred but not required - Exposure to Spark / PySpark or large-scale data processing is a strong plus - Understanding of marketing data systems (e.g., Salesforce, Marketo, HubSpot) is a plus Required Skills: Data engineering, SQL, Python, ETL pipelines, Data modeling, Lakehouse architecture, Spark, Marketing data systems, Analytical skills