Job DescriptionResponsibilities:
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- Technology partner certifications: Work through structured certification programs with our technology partners across martech platforms and marketing data tools, building real working proficiency rather than surface-level exposure. N
- Data querying and structuring: Get hands-on with SQL and structured data work, writing queries, understanding joins and aggregations, and learning how marketing data is organized and modeled. N
- Pipeline and integration exposure: Build working familiarity with how marketing data moves between systems, covering pipeline concepts, API-based integration, and tool categories like data warehouses and reverse-ETL. N
- Scripting for data work: Use Python or similar scripting to clean, transform, and work with marketing data, learning tools like pandas as you go. N
- Data quality practice: Learn to spot and fix data quality issues, inconsistent records, broken mappings, and gaps in how data flows into the places marketing teams use it. N
- Market and use-case research:



Investigate open problems and emerging use cases across the martech and data landscape to help our team understand what's possible and where the gaps are. N
- Solution curation support: Help shape and evaluate the solutions and services we consider bringing to clients, based on your research and certification work. N
- Writing and content contribution: Turn your research into written output, internal notes that inform our thinking, and external content such as newsletters, articles, and whitepapers. N
- Guided exposure to client work: You won't be placed directly on client engagements at this stage, but you'll get a real glimpse of client problems as you assist the team with research tied to active client challenges. N

nQualifications:
NThe primary profile: technically strong, recent to marketing
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- Pursuing or recently completed a Master's in Computer Science, Data Science, or a related engineering discipline. N
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📌 Marketing Data Engineering Intern (Karnataka)
🏢 Martechture
📍 Karnataka