Data Platform Engineer
- Compensation
- Not disclosed
- Location
- Brisbane, QLD, au
- Work setup
- Hybrid
- Seniority
- Senior
- Employment
- Contract
- Experience
- Not specified
- Category
- Data engineering
- Posted
Skills
Nice to have
- Why NCS?
- This is a place for people who like to get stuck in, bring ideas to life and make things happen. You'll work alongside experienced people who care about what they do, contribute to meaningful work and
- Ready to make extraordinary happen?
- We'd love to hear from you.
- We celebrate diversity and inclusion
- We value different perspectives, experiences and strengths our people bring. We're committed to an inclusive workplace where everyone has the opportunity to contribute, grow and succeed, and to provid
- Important information
- Applicants will need valid Australian work rights and may be required to undergo relevant background, probity and police checks.
- Agencies: NCS accepts candidate submissions only from agencies on our preferred supplier panel through the NCS Agency Portal.
Full description
We are seeking a Data Platform Engineer with strong quality engineering and automation expertise to support the development, validation, and reliability of large-scale data platforms. This role will focus on Databricks Lakehouse, PySpark, SQL, distributed data pipelines, event-driven architectures, and cloud-based data ecosystems, while also supporting automated testing, data validation, CI/CD quality gates, and platform resilience.
The successful candidate will play a key role in ensuring end-to-end data integrity across complex systems, validating data flows between applications and data platforms, and supporting performance, scalability, and reliability initiatives. Working closely with cross-functional teams, the individual will leverage strong Databricks, Python, and SQL expertise to investigate data quality issues, validate platform behaviour, and contribute to the continuous improvement of automation and engineering practices.
This is a hands-on technical role suited to a data engineering professional who can operate independently, collaborate across multiple teams, and apply quality engineering principles within a modern data platform environment. While testing and automation experience are important, the primary focus is deep expertise in Databricks, Python, SQL, and data platform engineering.
Responsibilities
- Design, develop, and maintain automated test frameworks and test suites.
- Build and enhance quality gates within GitLab CI/CD pipelines.
- Perform end-to-end testing of complex distributed data flows.
- Validate data integrity across RabbitMQ, Databricks Lakehouse, Lakebase, and Elasticsearch platforms.
- Conduct functional, integration, regression, and data validation testing.
- Collaborate with developers, platform engineers, and fellow SDETs to ensure seamless system integration.
- Coordinate cross-team testing activities across multiple application teams.
- Design and execute load, performance, and scalability testing strategies.
- Perform chaos testing and resilience validation of distributed systems.
- Investigate and troubleshoot data discrepancies across multiple storage systems.
- Contribute to continuous improvement of test automation practices and quality engineering standards.
- Proven experience as a Senior Data Engineer, Data Platform Engineer, SDET, Data Quality Engineer, or similar technical role.
- Strong hands-on experience with Python, PySpark, and SQL in enterprise-scale environments.
- Demonstrated experience working with Databricks Lakehouse and large-scale distributed data processing platforms.
- Experience validating and testing complex data pipelines, data integrations, and distributed systems.
- Strong understanding of data quality, data validation, and automated testing methodologies.