Senior Data Engineer
Australia & New Zealand
We proudly support the lives of creative professionals all over the world, from web developers and graphic designers, to marketers, videographers, photographers and more. We’ve built a community where anyone can get their creative projects done, and where creators bring their ideas to life and in the process, earn a living doing what they love.
We’re a global values led company, blending purpose and profit, and a passionate B Corp we are committed to making a positive impact on the communities we engage in. We have long embraced flexible ways of working, and we’re proud of how we keep our global team connected. Our roles can be based across Australia, New Zealand and Mexico.
You can read more about us on our company blog, including news of our acquisition by Shutterstock Inc in 2024.
About the roleAs a Senior Data Engineer at Envato, you will be responsible for building and operating the core systems that move data from source to warehouse, ensuring our platforms remain reliable, scalable, and secure.
You will work within the Data Engineering team in a DevOps-style environment where you support and run everything you build. The focus of this role is on the platform side of data engineering: infrastructure, orchestration, and ingestion. While you will collaborate with Analytics Engineers, you will not be responsible for business-facing data modelling or analytics.
This role is a great fit for an engineer who enjoys building the systems and pipelines that enable others to work with data. You will work across a modern data stack—including AWS, Terraform, Airflow, and Snowflake—to ensure data flows reliably and securely into our platform, forming a stable foundation for data across the business.
What you'll be doing
- Write high-quality, well-tested, and documented infrastructure code using Terraform.
- Build and maintain internal tooling, Docker images, and shared utilities for data workflows using Python and SQL.
- Utilise Git-based version control and CI/CD tooling (e.g., GitHub Actions, Terraform Cloud) to deliver platform changes.
- Own the end-to-end data ingestion layer, using tools like Fivetran and custom Python pipelines, from source systems to the warehouse.
- Configure and maintain Airflow DAGs, ensuring reliable scheduling, and contribute to the operation of cloud data warehouses like Redshift and Snowflake.
- Translate stakeholder needs into actionable infrastructure solutions, clearly communicating trade-offs and delivery plans.
- Actively participate in planning sessions and retrospectives to align on scope and delivery priorities, while maintaining up-to-date documentation.
- Debug and resolve issues across infrastructure, orchestration, and ingestion systems, participating in incident response and post-incident reviews.
- Continuously evaluate solutions to improve the performance and cost-effectiveness of platform components and data workflows.
- Collaborate closely with Analytics Engineering and other teams, sharing knowledge and providing constructive code reviews to promote best practices.
About you
- You likely have 5 years of experience in data or software engineering, with a distinct focus on infrastructure, ingestion, and orchestration.
- High proficiency with Infrastructure as Code (Terraform) and cloud-native environments, specifically AWS.
- Hands-on experience using Airflow for orchestration and Python for building ingestion tools and automation.
- Strong comfort working with SQL in data warehouses such as Redshift or Snowflake, and familiarity with dbt.
- Proven experience operating production-grade data pipelines, encompassing both managed connectors and custom-coded solutions.
- Deep understanding of data engineering fundamentals, including ingestion best practices, platform reliability, and system observability.
- Experience taking end-to-end ownership of platform components, including their deployment, monitoring, debugging, and cost management.
- Demonstrated ability to contribute to technical designs (e.g., RFCs) and evaluate trade-offs in architecture and tooling.
- Excellent communication and collaboration skills, with experience working effectively across engineering, analytics, and product teams.
- A thoughtful approach that prioritises automation and operational excellence, balancing short-term delivery with long-term platform sustainability.
• Flexible Working - Remote-first with flexibility for you to manage work and life as you need. • Work from Anywhere - Apply to work in another location for up to 3 months per calendar year.• Connection Budget - An annual budget to connect with the team IRL where and when possible.• Learning Budget - Study leave and an annual budget for you to put towards your learning and development.• Home Office Allowance - A contribution towards your set-up and a monthly allowance to support work from home costs.• Wellbeing - Access to a holistic assistance program that provides support in many areas of life and health.• Volunteer Leave - 2 days per calendar year to volunteer and give back to the community.• Parental Leave - 20 weeks paid primary carer leave, and 6 weeks paid secondary carers leave.
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* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: Airflow Architecture AWS CI/CD Data pipelines dbt DevOps Docker Engineering FiveTran Git GitHub Pipelines Privacy Python Redshift Research Snowflake SQL Terraform
Perks/benefits: Career development Flex hours Home office stipend Parental leave Wellness
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