We are looking for an experienced Senior Data Engineer / Staff Engineer to join our data engineering team and help build highly scalable, reliable, and cloud-native data platforms on AWS. The role requires solid expertise in Python, SQL, AWS data services, distributed data processing, and modern engineering practices, with the ability to contribute to solution design and technical direction.

Key Responsibilities

- Architect and develop robust data ingestion, transformation, and processing pipelines capable of handling large and complex datasets.
- Develop scalable data platforms using AWS Glue, Amazon Redshift, Amazon Athena, AWS Step Functions, and other AWS-native technologies.
- Design and implement both batch and real-time data processing frameworks using Kafka, Apache Flink, and related technologies.
- Build APIs, automation frameworks, and reusable services to support data engineering and platform capabilities.
- Establish effective practices for data quality, governance, security, lineage, and compliance.
- Develop and optimise logical, semantic, and physical data models based on business and analytical requirements.
- Work closely with architects, product teams, business stakeholders, and engineering squads to translate requirements into scalable technical solutions.
- Drive engineering automation through CI/CD and DevOps practices, leveraging Jenkins, Git, Docker, and Kubernetes.
- Analyse platform performance, identify bottlenecks, and implement improvements for scalability, availability, and reliability.
- Participate in architecture discussions,



technical design reviews, and engineering standards.
- Provide technical leadership and mentorship to other members of the data engineering team.

Essential Skills

- Strong commercial experience in Python and SQL.
- Hands-on experience developing data solutions on AWS.
- Strong experience with AWS Glue, Redshift, Athena, and Step Functions.
- Solid understanding of ETL/ELT, data pipelines, data integration, and distributed processing.
- Practical experience with Kafka and/or Apache Flink.
- Strong knowledge of data modelling, data quality, governance, and security.
- Experience with Jenkins, Git, Docker, Kubernetes, IAM, and Vault.
- Experience working with APIs and automation frameworks.
- Strong understanding of Agile development and modern software engineering practices.

Desirable Experience

- Experience with Apache Iceberg and Data Lakehouse architectures.
- Exposure to real-time analytics and event-driven architectures.
- Experience working with high-volume or enterprise-scale data platforms.
- Background in financial services or other highly regulated environments.
- Experience contributing to cloud data architecture and technical strategy.

What We’re Looking For

The successful candidate will be someone who can operate beyond day-to-day pipeline development, taking ownership of technical design, platform scalability, engineering standards, and complex data problems while working closely with multiple stakeholders and mentoring other engineers.

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📌 AWS Data Engineer (New South Wales)
🏢 Silverlink Technologies
📍 New South Wales