Principal Data Engineer

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

Job summary

M&T Resources is seeking a Principal Data Engineer & Designer to architect and deliver scalable, secure data solutions on AWS in a high-performance environment.

This 50/50 hands-on role focuses on building data pipelines, data lakehouse patterns, and governance, while mentoring engineers and collaborating with stakeholders.

You’ll leverage Python, Spark, dbt, Airflow and SageMaker to create future-ready data products and drive DataOps across the team.

Qualifications

• 10+ years of data engineering experience.
• Strong AWS data platform and pipeline experience.
• Proficient in Python, Spark, dbt and Airflow.
• Knowledge of distributed systems and data architecture.
• Experience with Redshift, Iceberg and data lakehouse patterns.
• Proven leadership in 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 data solutions.
• Drive DataOps, CI/CD, automation and observability.
• Embed security, privacy, governance and reliability.

Skills

Data engineering

AWS data platform

Python

Spark

dbt

Airflow

Data architecture

Data governance

Tools

SageMaker

Redshift

Iceberg

Job description

Principal Data Engineer & Designer

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 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.