Senior Data Engineer (AWS / Spark)

Xpert Consulting T/A Novon; Australia; On-site; AUD 90,000 - 150,000; Full time

Job summary

Xpert Consulting T/A Novon is seeking a seasoned Data Engineer to design, build, and optimise large-scale data pipelines using Spark and PySpark in an enterprise environment.

You'll work with AWS-native data solutions including Glue, Glue Catalog, S3, Airflow, DBT, and Starburst/Presto, migrating legacy assets to modern cloud architectures, ensuring data quality, performance, and scalable delivery while collaborating closely with architects and stakeholders.

Qualifications

• Minimum 5 years as a Data Engineer in enterprise-scale environments.
• Hands-on Spark and PySpark experience.
• Strong AWS data ecosystem knowledge (Glue, S3, Starburst/Presto, Airflow, DBT).

Responsibilities

• Design, build, and optimise data pipelines using Spark / PySpark.
• Develop and maintain AWS-native data solutions (Glue, Glue Catalog, S3, Airflow, DBT).
• Support migration of legacy pipelines to modern cloud architectures.
• Implement data quality, monitoring, and performance optimization.
• Collaborate with architects, analysts, and stakeholders to deliver scalable data solutions.

Skills

Spark

PySpark

AWS Cloud

Data Pipelines

Stakeholder Communication

Tools

AWS Glue

Glue Catalog

Amazon S3

Airflow

DBT

Starburst

Presto

Job description

Key Responsibilities

Design, build, and optimise data pipelines using Spark / PySpark, Design, develop and maintain AWS-native data solutions leveraging services including Glue, Glue Catalog, S3, Airflow, DBT, and Starburst/Presto. Supporting large-scale migration of legacy and bespoke data pipelines. Developing robust ETL and ELT processes using modern data engineering practices. Support the migration of existing data assets into modern cloud-based architectures. Contributing to data platform optimisation, automation, and continuous improvement initiatives. Implement data quality, monitoring, and performance optimisation practices. Work closely with architects, analysts, and stakeholders to deliver reliable and scalable data solutions. Troubleshoot complex data engineering issues and identify opportunities for improvement. Contribute to technical design discussions and engineering best practices. Provide consulting expertise and communicate effectively with customer stakeholders.

What We’re Looking For

Core Skills and Experience Minimum 5 years working as a Data Engineer in enterprise-scale environments. Hands‑on experience building pipelines with Spark and PySpark. Strong knowledge of the AWS data ecosystem, including: AWS Glue Glue Catalog Amazon S3 Starburst / Presto Apache Airflow DBT services for Transformation Experience designing and supporting complex data pipelines and data integration solutions. Strong understanding of cloud-based data architectures and engineering best practices. Excellent problem‑solving and analytical skills. Strong stakeholder engagement and communication skills. Customer‑focused mindset with the ability to work directly with senior business and technical stakeholders. Desirable Financial Services industry experience. Consulting experience within client‑facing environments. Experience delivering large‑scale cloud migration or modernisation programs. Exposure to modern data lake, lakehouse, and distributed data processing architectures.

You’ll join a team that values

Be Innovative. Be Curious. Be Humble. Be Yourself.

Expect a collaborative culture, meaningful projects, and a strong focus on learning and growth.

You’ll have the opportunity to work alongside highly skilled consultants, contribute to impactful client outcomes, and continue developing your expertise within a supportive and inclusive environment.

We’d love to hear from passionate

If you’re passionate about modern data engineering, cloud technologies, and helping organisations unlock value from their data, we’d love t