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Liven (liven.love)

Senior Data Engineer

Sorry, this job was removed at 10:19 a.m. (IST) on Wednesday, Jan 14, 2026
In-Office or Remote
2 Locations
In-Office or Remote
2 Locations

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Join the revolution in hospitality tech!


Liven is a leading global data, technology, and customer experience provider for the hospitality industry. From humble beginnings, we have grown to 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.


At Liven, our platform is built to help hospitality businesses save more and work smarter by seamlessly integrating every aspect of their operations — from ordering and payments to back-of-house management.

Driven by a deep passion for the hospitality industry, we continuously innovate to elevate the experience for both venues and their guests. Our solutions are powered by AI-enriched insights and automated workflows, enabling smarter decision-making and smoother operations at scale.

We’re proud to be an AI-first organisation. By automating repetitive tasks, we free up space for our teams — and our customers — to focus on what truly matters: solving complex problems, delighting guests, and driving meaningful growth.
Key Milestones:

  • Expansion: Acquired OrderUpAbacusZeemart, Copper and Nomnie forming Asia Pacific’s largest end-to-end group in hospitality technology.
  • Global Reach: Headquartered across major cities including Melbourne, Brisbane, Sydney, Singapore, Bali, Jakarta, New York, and India.

If you're someone who thrives on creativity, bold thinking, and using technology to make things better, faster, and smarter — you’ll feel right at home here.


Here’s a quick glimpse of Liven: 

  • You can visit Career 
  • You can visit LinkedIn 
  • You can Visit Blog
  • Acquisition News

About the role
As a Senior Data Engineer at Liven, you'll be a critical part of our Data & Analytics team—building and maintaining scalable ELT pipelines, ensuring data reliability, and enabling impactful decision-making across the company. This role blends engineering excellence with business insight, giving you the opportunity to influence how data is used company-wide.

You’ll be working with modern open-source tools and cloud-based data platforms, with the autonomy to shape the future of 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.



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