Data Engineer

Data Engineer

About RevX

RevX helps app businesses acquire and reengage users via programmatic to retain, monetize, and accelerate revenue. We're all about taking your app businesses to a new growth level. We rely on data science, innovative technology, and AI, and a skilled team, to create and deliver seamless ad experiences to delight your app users. That’s why RevX is the ideal partner for app marketers that demand trustworthy insights, a hands-on team, and a commitment to growth. We help you build sound mobile strategies, combining programmatic UA, app re engagement, and performance branding to drive real and verifiable results so you can scale your business : with real users, high retention, and incremental revenue.

About the Role

We are seeking a forward-thinking Data Engineer who can bridge the gap between traditional data pipelines and modern Generative AI (GenAI) -enabled analytics tools. You'll design intelligent internal analytics systems using SQL, automation platforms like n8n , BI tools like Looker , and GenAI interfaces such as ChatGPT , Gemini , or LangChain .

This is a unique opportunity to innovate at the intersection of data engineering , AI , and product analytics .

Key Responsibilities

• Design, build, and maintain analytics workflows / tools leveraging GenAI platforms (e.g., ChatGPT, Gemini etc.) and automation tools (e.g., n8n , Looker etc.).
• Collaborate with product, marketing, and engineering teams to identify and deliver data-driven insights.
• Use SQL to query data from data warehouses (BigQuery, Redshift, Snowflake, etc.) and transform it for analysis or reporting.
• Build automated reporting and insight generation systems using visual dashboards and GenAI-based interfaces.
• Evaluate GenAI tools and APIs for applicability in data analytics workflows.
• Explore use cases where GenAI can assist in natural language querying , automated summarization , and explanatory analytics .
• Work closely with business teams to enable self-service analytics via intuitive GenAI-powered interfaces.
• Design and maintain robust data pipelines to ensure timely and accurate ingestion, transformation, and availability of data across systems.
• Implement best practices in data modeling, testing, and monitoring to ensure data quality and reliability in analytics workflows.

Requirements

Nice to Have

Why Join Us?

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