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.
#J-*****-Ljbffr

📌 Aws Data Engineer (Sydney)
🏢 Silverlink Technologies
📍 Sydney