Senior Data Engineer

Overview

Liven is a leading global data, technology, and customer experience provider for the hospitality industry. We serve over 6,000 venues and millions of diners across Australia, the USA, and Southeast Asia, processing over 120 million transactions worth more than $3 billion (AUD) annually. Our platform helps hospitality businesses save more and work smarter by integrating ordering, payments, and back-of-house management. We are an AI-first organisation powered by AI-enriched insights and automated workflows to enable smarter decision-making and smoother operations at scale. By automating repetitive tasks, we free up space for our teams and customers to focus on solving complex problems and driving growth.

Key milestones include acquisitions forming Asia Pacific’s largest end-to-end group in hospitality technology and a global reach with a presence in major cities such as Melbourne, Brisbane, Sydney, Singapore, Bali, Jakarta, New York, and India.

Role Snapshot

Senior Data Engineer at Liven is a key member of the Data & Analytics team—responsible for building and maintaining scalable ELT pipelines, ensuring data reliability, and enabling impactful decision-making company-wide. This role blends engineering excellence with business insight and provides the opportunity to influence how data is used across the organisation. You will work with modern open-source tools and cloud-based data platforms, with the autonomy to shape Liven’s data architecture.

What You'll Do

• 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.

Qualifications

Must-Have Experience

• 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.

Should-Have Experience

• 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.

Good to Have

• 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.

Additional Details

• Seniority level: Mid-Senior level
• Employment type: Full-time
• Job function: Information Technology
• Industries: Embedded Software Products

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