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Data Platform Engineer

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Work setting
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Work setup in the employer’s posting: On-site
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Employment type in the employer’s posting: Contract
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Before you apply

Work authorization
Must already have the right to work in AustraliaApplicants will need valid Australian work rights

What you’ll work on

Full posting
  • 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

From the employer’s posting
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.

What you’ll bring

All qualifications

Core experience

  • 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.
Qualification wording
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.
Apply at NCS Australia

Posting record

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Actively hiringFirst seen by us 2 days ago, still listed, and not a repost of an earlier posting.

Status in our records
Live
First seen by us
Nov 2, 20262 days ago
Recorded sightings
3
Last seen by us
Nov 4, 2026

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.

How this job compares

Time since we first saw it

Day 2

Early. Similar jobs usually come down between day 5 and day 54.

From 10,733 similar postings that came down. Coming down is not always a hire.

NCS Australia is hiring

7 open jobs

Open jobs by the week we first saw them, last 12 weeks.

  • Data Engineer hiring is picking up
  • Takes jobs down at a usual pace
Hiring record

See how this role fits your experience

Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.

  • C#
  • Python
  • SQL
  • Databricks
  • Elasticsearch
  • Terraform
  • PySpark
Where the posting names them
- 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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About the role

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.

US government figures for database architects

Median yearly pay, May 2025
$139,500
Expected change, 2025 to 2035
9.4% more jobsagainst 3.5% for all jobs

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.

Job description

View original posting ↗

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.

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.

Qualifications

  • 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.
  • 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.
  • Strong analytical, problem-solving, and troubleshooting skills.
  • Excellent communication and stakeholder management skills with the ability to collaborate across multiple teams.
  • Desirable Qualifications & Experience

  • Experience with performance, load, scalability, resilience, and chaos testing.
  • Experience working within cloud-native and modern data platform environments.
  • Exposure to DevOps and Site Reliability Engineering (SRE) practices.
  • Knowledge of C# and .NET technologies.
  • Experience working in Agile delivery environments.
  • Relevant certifications in Databricks, Cloud Technologies, or Data Engineering would be advantageous.

Additional Information

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.

Company Description

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.

Source details

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Brisbane, QLD, Australia

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