Data Engineer

At SiteMinder, we believe our success comes from our people. We build diverse, inclusive teams where different voices, backgrounds and perspectives are valued. Our differences drive innovation for our customers, and our people bring the ideas, expertise and energy that help us keep moving forward. We’re better together.

What we do...

Right now, somewhere in the world, a hotel is taking a booking or increasing their revenue through technology you could help build. SiteMinder is the world’s leading hotel commerce platform. For more than 20 years, we’ve helped hotels attract guests, maximise revenue, forecast demand and perform at their best. Today, our platform supports 56,000+ hotels in 150+ countries, connects to 3,000+ partners and powers more than 140m reservations and AU$85 billion+ in hotel revenue each year.

That’s the kind of impact your work can have here. You’ll solve meaningful challenges with AI, simplify complexity and build solutions that help hotels perform. Supported by clear purpose, a strong platform and teams who care about what they’re building, you’ll have the opportunity to shape the future of an industry that never stands still.

About the Data Engineer role...

The Data & Business Systems team at SiteMinder serves as the central data hub supporting all reporting and insights initiatives across the company. We are looking for an experienced Data Engineer proficient in DBT, Databricks, SQL, and Python to join our team. In this role, you will be a key member of the core data engineering group, driving data engineering and reporting needs that power our business intelligence and reporting capabilities. You will work extensively on Databricks and AWS environments to design, build, and maintain robust data pipelines and models. This is a highly hands-on position, with approximately 70% focus on data engineering projects and 30% on data operations.

What you will do...

Dedicate your time to developing, testing, and maintaining high-quality, scalable ETL/ELT data pipelines using Python, PySpark, and Databricks on AWS

You will lead the development of new data features and services across the full product lifecycle, from architectural design to deployment including technologies like Terraform, spark structured streaming, dlt, etc.

Create CI/CD controlled data engineering deployments using Databricks Asset Bundles and leverage Databricks serverless compute with cost optimization techniques to deliver performant data products

Work within a fast-paced agile team, collaborating closely with Product Managers, Data Scientists, and fellow engineers to solve complex data challenges. You will help ensure the quality, integrity, and security of data throughout the data lifecycle, implementing best practices in data governance

Take technical ownership of major components of our data platform architecture. You will lead design discussions, ensuring our data systems are secure, scalable, and maintainable

Analyse workloads, queries, clusters/warehouses, jobs, and services to identify inefficiencies and savings opportunities

Implement continuous monitoring and intelligence dashboards for cost and performance optimization

Stay ahead of new Snowflake/Databricks features and translate them into marketable product differentiators

What you have...

Extensive experience with data engineering; DataBricks & DBT (Mandatory)

Proven expertise in platform internals:

Databricks : clusters, jobs, Delta Lake, Spark optimization, autoscaling, Unity Catalog

Strong SQL + Python skills for automation, monitoring, and recommendation logic

Experience working with AWS data services

Experience with frameworks like Terraform & Airflow

Track record of delivering performance gains and cost savings through platform-level optimizations

Startup mindset: hands-on, automation-driven, customer-value obsessed