Senior Data Platform Engineer

**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 OrderUp, Abacus, Zeemart, 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**:

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- You can Visit Blog
- Acquisition News

**About the role**

As a **Senior Data Platform Engineer**, you will be the technical owner of Liven’s data platform infrastructure—driving automation, scalability, and resilience across our data workflows. Sitting at the intersection of DevOps and Data Engineering, this role is critical in enabling our teams to ship faster, fail less, and derive more value from our data ecosystem.

You’ll work closely with data engineers, analysts, product managers, and software engineers to build and operate a modern, secure, and scalable data platform that supports everything from machine learning pipelines to real-time analytics.

**What you'll do**
- Own and operate the end-to-end **data infrastructure**, ensuring performance, reliability, and scalability.
- Design and implement **CI/CD pipelines** specifically for data workflows and tooling.
- Deploy and manage tools like **Airbyte**, **Prefect**, and **Superset** using **Docker** and **Kubernetes**.
- Set up and maintain **monitoring, secrets management, and alerting** systems to ensure platform health and security.
- Manage and scale **Kafka**, **Spark**, or **DuckDB** clusters to support real-time and batch data workloads.
- Explore and maintain **self-hosted tools** like **dbt Cloud**, ensuring smooth integration and performance.
- Use **Infrastructure-as-Code** tools like **Terraform** or **Helm** to automate provisioning and configuration.
- Administer observability stacks such as **Grafana** and **Prometheus** for infrastructure visibility.
- Implement secure **access control**, **role-based permissions**, and ensure compliance with **GDPR**, **HIPAA**, and internal data governance standards.
- Collaborate across teams to support data engineers, analysts, and developers with reliable infrastructure and workflow tooling.
- Steer clear of proprietary infrastructure platforms like **AWS Glue** or **Azure Synapse** (we’re staying open-source/cloud-native for now).

**Qualifications**
- 5-8 years of experience in DataOps, DevOps, or Platform Engineering roles.
- Proficiency with modern data stack components (e.g., Airflow, dbt, Kafka, Databricks, Redshift).
- Solid understanding of cloud platforms (AWS or GCP).
- Strong communication skills to collaborate across product, data science, and engineering teams.
- Bias for ownership, automation, and proactive resolution.

**Good to Have**
- Experience with Infrastructure-as-Code tools like **Terraform** or **Helm** for managing Kubernetes and cloud resources.
- Familiarity with administering **Grafana**, **Prometheus**, or similar observability stacks.
- Exposure to **GitOps** methodologies and tools like **Argo CD** or **Flux**.
- Hands-on experience with self-hosted or hybrid setups of tools like **dbt Cloud**.
- Understanding of **auto-scaling** strategies for distributed systems (Kafka, Spark, DuckDB).
- Experience contributing to platform or DevOps initiatives in a **data-heavy environment**.