Location: Sydney, NSWExperience: 9–14 YearsEmployment Type: Full-TimeEligibility: Australian Citizens & Permanent Residents (PR) OnlySponsorship: Not AvailableAbout the RoleWe are seeking an experienced Data Engineer with expertise in AWS SageMaker Unified Studio to design and build scalable data platforms, real-time and batch data pipelines, and enterprise data solutions on AWS.Key ResponsibilitiesDesign and develop batch and real-time data ingestion frameworks.Build ETL/ELT pipelines using Python, PySpark, SQL, and Apache Airflow (MWAA).
Develop streaming solutions using AWS Kinesis, Kafka, or similar technologies.Build and manage solutions in AWS SageMaker Unified Studio, including ML pipelines, data processing, governance, and project setup.Develop data solutions using Amazon Redshift, S3, Glue, Lambda, and DynamoDB.Manage Airflow workflows, monitoring, logging, and performance optimisation.Collaborate with Data Engineers, Data Scientists,



and Architects to deliver scalable AWS data solutions.Required Skills9–14 years of Data Engineering experience.Strong hands-on experience with:AWS SageMaker Unified StudioAWSPythonPySparkSQLApache Airflow (MWAA)Amazon RedshiftExperience with AWS Kinesis, Apache Kafka, or similar streaming platforms.Strong knowledge of AWS services including S3, Glue, Lambda, DynamoDB, CloudWatch, SQS, SNS, API Gateway, and IAM.Experience with relational and NoSQL databases (Oracle, RDS, Redshift, MongoDB, Snowflake, DynamoDB).
Valuable understanding of Data Warehousing, Data Lakehouse, Git, CI/CD, Docker, and Infrastructure as Code (Terraform/CloudFormation).
Preferred SkillsExperience with Machine Learning pipelines, MLOps, and Generative AI in SageMaker.Data Modelling experience.Enterprise-scale AWS implementation experience.EligibilityAustralian Citizens & Permanent Residents (PR) only.Candidates must be currently residing in Australia.No visa sponsorship is available.
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📌 Data Engineer – Aws Sagemaker Unified Studio-Australia Only (Melbourne)
🏢 The HR Ally
📍 Melbourne