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Data Engineer (AWS / Spark)

Novon
Sydney NSW

Quick Apply

Job Details

Full-time
4 hours ago

Qualifications

AWS
Analysis skills
Data pipeline
S3
Financial services
Apache
Communication skills

Full Job Description

Data Engineer (AWS / Spark)
Location: Sydney (Hybrid – Minimum 3 Days Onsite)

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 outcomes for our customers, our teams work on interesting and diverse projects with organisations ranging from large 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 while working alongside high-performing engineering and consulting teams.

This role is focused on:

Designing, developing, and maintaining scalable data pipelines using Spark and PySpark.
Building cloud-native data solutions within AWS data platforms.
Supporting large-scale migration of legacy and bespoke data pipelines.
Developing robust ETL and ELT processes using modern data engineering practices.
Working with business and technical stakeholders to understand requirements and deliver high-quality solutions.
Contributing to data platform optimisation, automation, and continuous improvement initiatives.
Collaborating within Agile delivery teams to deliver business-critical outcomes.

Key Responsibilities

Design, build, and optimise data pipelines using Spark, PySpark, and Java.
Develop and maintain AWS-native data solutions leveraging services including Glue, Glue Catalog, S3, Airflow, DBT, and Starburst/Presto.
Support the migration of existing data assets into modern cloud-based architectures.
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

Strong experience as a Data Engineer in enterprise-scale environments.
Hands-on experience with Spark, PySpark, and Java.
Strong knowledge of the AWS data ecosystem, including:

o AWS Glue
o Glue Catalog
o Amazon S3
o Starburst / Presto
o Apache Airflow
o DBT

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 to hear from you.

Quick Apply

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