Senior Data Engineer (AWS / Spark)

NOVON; Sydney; On-site; AUD 120,000 - 180,000; Full time

Job summary

NOVON in Sydney seeks experienced Data Engineers (Mid-Level and Senior) to join our Data Practice and support a major transformation program within a leading financial services organisation.

You will design, build and modernise hundreds of data pipelines, creating scalable cloud-native data solutions on AWS while collaborating with a high-performing team of engineers and consultants.

Qualifications

• 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 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.

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.

Skills

Spark

PySpark

AWS

Airflow

DBT

ETL/ELT

Tools

AWS Glue

Glue Catalog

Amazon S3

Starburst/Presto

Airflow

DBT

Job description

Novon is a Data, Engineering and Business Services Consulting Company headquartered in Sydney, partnering with blue-chip (ASX50) organisations to solve complex business challenges through data and technology.

With close to 100 Consultants and more than 10 years delivering successful data projects for our customers, our teams work on complex and diverse projects with organisations ranging from the largest local enterprises to SMEs and start-ups across multiple industries.

We are currently seeking experienced Data Engineers (Mid-Level and Senior) to join our growing Data Practice and support a major data transformation program within a leading financial services organisation.

This opportunity will see you contribute to the migration and modernisation of hundreds of bespoke data pipelines, helping to build scalable, cloud-native data solutions on AWS cloud while working alongside a high-performing engineering and consulting team.

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.

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