Senior Data Engineer

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August 27

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Liven

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SaaS • Hospitality

Liven is a comprehensive hospitality platform designed to streamline operations, increase profitability, and enhance guest experiences for venues. It supports over 6,000 venues across Asia Pacific, including cafes, restaurants, and grocery stores, providing solutions that cover everything from ordering and payments to kitchen management and customer loyalty. With advanced POS systems and digital tools, Liven aims to reduce operational costs while driving customer engagement. The system is user-friendly and adaptable, working seamlessly across various environments such as quick-service restaurants, fine dining, and more. Liven is known for its innovative approach in the hospitality industry, helping businesses save costs and improve operational efficiency.

51 - 200 employees

☁️ SaaS

📋 Description

• Join the revolution in hospitality tech! Liven is a leading global data, technology, and customer experience provider for the hospitality industry. • Build and maintain scalable ELT pipelines, ensuring data reliability, and enabling impactful decision-making across the company. • Work with modern open-source tools and cloud-based data platforms, with autonomy to shape Liven’s data architecture. • Design, develop, and maintain scalable ELT pipelines using Python and SQL . • Own and manage data workflows using tools like Airbyte or Meltano . • Build and maintain robust dbt models and support analytics across the company. • Operate and improve data infrastructure using DevOps practices and CI/CD pipelines . • Collaborate with cross-functional teams to define metrics, model data, and deliver high-impact analytical outputs. • Manage and monitor DAGs in Prefect or Apache Airflow , ensuring data freshness and reliability. • Use Terraform and infrastructure-as-code principles to provision and manage cloud-based resources. • Support testing and monitoring using frameworks like Great Expectations (nice to have). • Contribute to data quality, governance, and documentation best practices. • Participate in a strong feedback culture, contributing to continuous improvement of data workflows and team practices.

🎯 Requirements

• 4–8 years in Data or Analytics Engineering, ideally in a startup or scale-up environment. • Strong hands-on skills with Python and SQL . • Deep experience with DevOps practices and operational ownership of tools like Airbyte or Meltano . • Solid understanding and experience with dbt . • Proven track record of building reliable, scalable pipelines in a modern cloud data stack. • Experience managing large DAGs using Prefect or Airflow . • Familiarity with Kafka and real-time pipeline architecture. • Experience using Terraform or other infrastructure-as-code tools. • Familiarity with ELT testing frameworks like Great Expectations . • Contributions to open-source data tools or frameworks. • Experience with proprietary ingestion tools like Fivetran or Segment .

🏖️ Benefits

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