Job Role : Data Engineer

Location : Sydney

Duration: 6 months extendable

Data Engineer (SSE / Staff Engineer)

Core Skills

Languages

- Python
- SQL

Data Technologies

- AWS Glue
- Redshift
- Athena
- Iceberg
- Flink
- Kafka
- Understanding of Big Data technologies

Cloud / Hosting

- AWS
- Understanding of network design
- AWS native services such as Step Functions

Data Engineering

- Data pipelines
- Airflow
- Data ingestion
- Data transformation
- Data governance
- Semantic and physical data modeling

APIs & Microservices

- RESTful services
- Automation scripts

DevOps

- CI/CD (Jenkins, Git)
- Docker
- Kubernetes
- IAM
- Vault
- Operations mindset

Security & Compliance

- Data governance
- Risk management

Agile Delivery

- Collaboration with squads and stakeholders

Role Overview We are seeking a highly skilled Data Engineer (SSE / Staff Engineer) to design, build, and maintain scalable data platforms and pipelines on AWS. The ideal candidate will have strong expertise in Python, SQL, cloud-native data technologies, and up-to-date data engineering practices.

Key Responsibilities

- Design and develop scalable data pipelines for ingestion, transformation, and processing of large-scale data.
- Build and maintain data solutions using AWS services such as Glue, Redshift, Athena, Step Functions, and related cloud-native services.
- Implement streaming and batch data processing solutions using technologies such as Kafka and Flink.




- Develop RESTful APIs and automation frameworks to support data services.
- Ensure data quality, governance, security, and compliance requirements are met.
- Create and maintain semantic and physical data models.
- Collaborate with product owners, architects, business stakeholders, and cross-functional squads.
- Implement CI/CD pipelines and DevOps best practices using Jenkins, Git, Docker, and Kubernetes.
- Monitor, troubleshoot, and optimize data platform performance and reliability.
- Contribute to architecture decisions and mentor junior engineers.

Required Qualifications

- Strong hands-on experience with Python and SQL.
- Experience with AWS data services including Glue, Redshift, Athena, and Step Functions.
- Knowledge of Kafka, Flink, and modern Big Data technologies.
- Experience designing data pipelines and ETL/ELT solutions.
- Understanding of data governance and data modeling principles.
- Hands-on experience with CI/CD, Docker, Kubernetes, IAM, and Vault.
- Strong problem-solving and stakeholder management skills.
- Experience working in Agile delivery environments.

Preferred Qualifications

- Experience with large-scale cloud data platforms.
- Knowledge of data lakehouse architectures and Apache Iceberg.
- Experience with streaming analytics and event-driven architectures.
- Prior experience in financial services or regulated industries.

📌 Data Engineer (Sydney)
🏢 ALOIS Australia
📍 Sydney