We are looking for an experiencedSenior Data Engineer / Staff Engineerto join our data engineering team and help build highly scalable, reliable, and cloud-native data platforms onAWS.
The role requires strong expertise inPython, 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 robustdata ingestion, transformation, and processing pipelinescapable of handling large and complex datasets.
Develop scalable data platforms usingAWS Glue, Amazon Redshift, Amazon Athena, AWS Step Functions, and other AWS-native technologies.
Design and implement bothbatch and real-time data processing frameworksusingKafka, Apache Flink, and related technologies.
Build APIs, automation frameworks, and reusable services to support data engineering and platform capabilities.
Establish effective practices fordata quality, governance, security, lineage, and compliance.
Develop and optimiselogical, semantic, and physical data modelsbased 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 throughCI/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 inPython and SQL.
Hands-on experience developing data solutions onAWS.
Strong experience withAWS Glue, Redshift, Athena, and Step Functions.
Solid understanding ofETL/ELT, data pipelines, data integration, and distributed processing.
Practical experience withKafka and/or Apache Flink.
Robust knowledge ofdata modelling, data quality, governance, and security.
Experience withJenkins, 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 withApache Iceberg and Data Lakehouse architectures.
Exposure toreal-time analytics and event-driven architectures.
Experience working with high-volume or enterprise-scale data platforms.
Background infinancial 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 oftechnical design, platform scalability, engineering standards, and complex data problemswhile working closely with multiple stakeholders and mentoring other engineers.
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📌 Aws Data Engineer (New South Wales)
🏢 Silverlink Technologies
📍 New South Wales