Data Engineer

• Design, build, and maintain scalable, fault-tolerant data pipelines (batch and/or streaming) for core business and product data.
• Ingest data from diverse sources including APIs, databases, event streams, and third-party services, ensuring high data quality and reliability.
• Design and manage data models and storage layers (data warehouses, data lakes) that support analytics and downstream use cases.
• Partner with analytics, product, and engineering teams to deliver clean, well-documented datasets that enable self-service analytics and experimentation.
• Implement monitoring, logging, and alerting to ensure pipeline reliability, performance, and cost efficiency.
• Enforce data governance best practices, including access control, privacy, documentation, and data lineage.

• Build and maintain data pipelines for marketing and analytics use cases
• Develop the data warehouse and analytics platform
• Work on data quality: monitoring, consistency, and completeness checks
• Integrate new data sources: APIs, internal databases, files, and event data
• Contribute to the semantic layer and prepare data for BI
• Work closely with analysts and business teams on reporting and analytical tasks

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Data Engineer

Data Engineer