Marketing Data Engineering Intern

Role Description 

We are seeking a Marketing Data Engineering Intern to support the launch of Campaign360, a strategic initiative to unify and standardize marketing campaign data across the organization. This role will help build a scalable, governed data foundation that integrates data from CRM, marketing automation, web analytics, and product systems into a single, reliable Campaign360 data model. The intern will work hands-on with modern data engineering tools in Microsoft Fabric, contributing to ETL pipelines, Lakehouse architecture, and curated datasets that power campaign performance reporting, funnel analytics, and pipeline attribution. This role offers exposure to end-to-end data engineering while partnering closely with Marketing and Analytics stakeholders. 

Key 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. 

Qualifications 

Required / Preferred Background 

• 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. 
• Coursework or project experience in data engineering, distributed data processing, or analytics engineering is a plus 
• 4 Days in Office - Arlington, VA

Technical Skills (academic or project-based experience acceptable) 

• Familiarity with SQL and data transformation concepts.

Experience with Python (pandas or PySpark preferred) 

• Exposure toETL/ELT pipelines, data modeling, or Lakehouse/data warehouse concepts.
• Understanding ofmarketing or customer data is a plus.
• Experience or interest in Microsoft Fabric, Power BI, or similar platforms is preferred but notrequired.

• 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 

Core Competencies 

• 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.