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Brisbane, QLD, Australia
Actively hiring, first seen by us 2 days agoWork setup in the employer’s posting: On-siteFrom the employer’s posting
Employment type in the employer’s posting: ContractFrom the employer’s posting
Applicants will need valid Australian work rights
Design, develop and maintain automated test frameworks and suites
Build and enhance quality gates in GitLab CI/CD pipelines
Validate data integrity across RabbitMQ, Databricks, Lakebase and Elasticsearch
Run load, performance, scalability and chaos testing of distributed systems
Investigate data discrepancies across multiple storage systems
Design, develop, and maintain automated test frameworks and test suites.
Build and enhance quality gates within GitLab CI/CD pipelines.
Validate data integrity across RabbitMQ, Databricks Lakehouse, Lakebase, and Elasticsearch platforms.
Design and execute load, performance, and scalability testing strategies.
Investigate and troubleshoot data discrepancies across multiple storage systems.
Proven experience as a Senior Data Engineer, Data Platform Engineer, SDET, Data Quality Engineer, or similar technical role.
Experience with performance, load, scalability, resilience, and chaos testing.
Demonstrated experience working with Databricks Lakehouse and large-scale distributed data processing platforms.
Experience working within cloud-native and modern data platform environments.
Experience validating and testing complex data pipelines, data integrations, and distributed systems.
Knowledge of C# and .NET technologies.
Actively hiringFirst seen by us 2 days ago, still listed, and not a repost of an earlier posting.
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
Day 2
Early. Similar jobs usually come down between day 5 and day 54.
From 10,736 similar postings that came down. Coming down is not always a hire.
7 open jobs
Open jobs by the week we first saw them, last 12 weeks.
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- Exposure to DevOps and Site Reliability Engineering (SRE) practices. - Knowledge of C# and .NET technologies. - Experience working in Agile delivery environments.
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.
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
- 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.
Job 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.
- 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.
- 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.
- Experience working in Agile delivery environments. - Relevant certifications in Databricks, Cloud Technologies, or Data Engineering would be advantageous. Additional Information
- Experience with GitLab CI/CD and implementing automated quality gates within deployment pipelines. - Experience working with Elasticsearch, event-driven architectures, and message brokers such as RabbitMQ. - Knowledge of Infrastructure as Code (IaC) tools, preferably Terraform.
- Experience working with Elasticsearch, event-driven architectures, and message brokers such as RabbitMQ. - Knowledge of Infrastructure as Code (IaC) tools, preferably Terraform. - Strong analytical, problem-solving, and troubleshooting skills.
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We file this job under Data Engineer, by the work the posting describes.
Data engineers build and run the pipelines that copy data out of apps and outside services into a warehouse or lake, and fix them when a source changes or a load fails.
Expect SQL, Python, a cloud platform, a scheduler such as Airflow, and often tools for large data such as Spark or Kafka.
An analytics engineer works one step later, turning the raw data a data engineer lands into clean tables people can query.
The government has no code for data engineers, so these figures are for the closest group, database architects, which includes data integration and data warehousing specialists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1243.
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
Desirable Qualifications & Experience
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 have the support to keep learning and grow your career. Whether you want to deepen your expertise, explore something new or take your career in a different direction, there's room to make it your own. We value Adventure, Excellence, Integrity, Ownership and Unity - bringing curiosity, collaboration and accountability to the way we work with our clients and each other.
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 providing equal employment opportunities and reasonable adjustments throughout the recruitment process.
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.
Make extraordinary happen
At NCS Australia, we’re the challenger alternative in technology services and consulting. With more than 47 years of Australian heritage, we partner with governments and leading organisations to solve complex challenges, embrace new opportunities and deliver outcomes that make a real difference.
Our people bring together expertise across technology, consulting, delivery, operations, sales and corporate functions. We work collaboratively, challenge the status quo and give our people the opportunity to make an impact — for our clients, our communities and each other.
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Brisbane, QLD, Australia
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