Principal Data Engineer

M&T Resources; Sydney; On-site; AUD 180,000 - 240,000; Full time

Job summary

M&T Resources in Sydney is seeking a Principal Data Engineer to architect and own scalable data solutions on AWS, balancing hands-on delivery with strategic design.

You will lead data platform architecture, build data lakehouse patterns, mentor engineers, and collaborate with stakeholders to deliver high-performance data products while embedding security and governance.

Qualifications

• 10+ years of data engineering experience.
• Strong AWS data platform and pipeline experience.
• Expertise in Python, Spark, dbt and Airflow.
• Strong knowledge of distributed systems and data architecture.
• Experience with Redshift, Iceberg and data lakehouse patterns.
• Proven experience leading data platform design and governance.

Responsibilities

• Lead end-to-end data platform architecture.
• Design scalable data lake and data mesh solutions.
• Build reusable data engineering frameworks and tools.
• Partner with stakeholders to deliver effective data solutions.
• Drive DataOps, CI/CD, automation and observability.
• Embed security, privacy, governance and reliability.

Skills

Data engineering

AWS

Python

Spark

dbt

Airflow

Redshift

Iceberg

Data governance

Data architecture

Data pipelines

Tools

AWS data stack

Job description

Principal Data Engineer

Are you ready to architect the future of data in a high-performance, mission-critical environment?

Come and join this established enterprise data team and lead and own the design and development of scalable, secure data solutions on AWS.

In this 50/50 hands on role you’ll architect and optimise data pipelines, mentor engineers, and collaborate with stakeholders to deliver high-performance, future-ready data products.

You’ll also have an opportunity to implement SageMaker!

Key responsibilities

• Lead end-to-end data platform architecture
• Design scalable data lake and data mesh solutions
• Build reusable data engineering frameworks and tools
• Partner with stakeholders to deliver effective data solutions
• Drive DataOps, CI/CD, automation and observability
• Embed security, privacy, governance and reliability

What we’re looking for

• 10+ years' data engineering experience.
• Strong AWS data platform and p ipeline experience.
• Expertise in Python, Spark, dbt and Airflow.
• Strong knowledge of distributed systems and data architecture.
• Experience with Redshift, Iceberg and data lakehouse patterns.
• Proven experience leading data platform design and governance.