In-Demand Machine learning engineer / data scientist Jobs

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AWS Data Engineer

Showtime Consulting -
Sydney NSW

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Job Details

Full-time
2 hours ago

Qualifications

Management
NoSQL
MongoDB
SQL
AWS
Machine learning
SDKs
APIs
Scalability
Agile
S3
Apache
Redshift
DynamoDB
AI
RDS database
Identity & access management

Full Job Description

Build real-time and batch data pipelines using AWS services
Develop scalable data platforms, governance and automation frameworks
Enable analytics, AI and machine learning through quality data solutions

Company Description
Showtime Consulting is a leading provider of Shielded Cloud and Digital Solutions. Based in Australia and New Zealand, we specialise in delivering secure, enterprise scale technology solutions across highly regulated environments. Our expertise spans cloud platforms, data engineering, and complex systems integration, supporting both commercial and government clients.

We partner with major organisations to deliver high impact programs that demand strong cloud, data, and analytics capability. Our focus is on building trusted relationships and delivering outcomes that enable long term business value.

The Role
We are seeking an experienced Senior AWS Data Engineer to join a high-performing data and analytics team. In this role, you will design, build, and support scalable data platforms, ingestion frameworks, and analytics solutions on AWS.

You will play a key role in developing real-time and batch data pipelines, implementing data governance and orchestration frameworks, and enabling advanced analytics, machine learning, and AI workloads. This is a hands-on role requiring strong AWS, Python, and data engineering expertise.

Key Responsibilities

Design and develop scalable data ingestion and processing frameworks across cloud environments.
Build and maintain real-time and batch data pipelines using AWS-native services.
Develop solutions using AWS SageMaker Unified Studio, including data discovery, engineering, governance, and analytics capabilities.
Create and optimise data transformation processes for large-scale analytical workloads.
Implement and manage workflow orchestration and pipeline automation.
Design and support data governance, monitoring, and observability solutions.
Build and maintain integrations with databases, APIs, streaming platforms, and external data sources.
Develop and manage data quality controls, validation processes, and operational monitoring.
Partner with analysts, data scientists, and business stakeholders to deliver data products and insights.
Contribute to engineering standards, reusable frameworks, and technical documentation.

What You'll Need

Strong experience designing and building cloud-based data platforms and pipelines.
Hands-on experience with AWS SageMaker Unified Studio, including data engineering and governance capabilities.
Strong Python development skills, including API integration and AWS SDK (Boto3).
Experience developing reusable ingestion frameworks across multiple data sources.
Strong experience with real-time and streaming data technologies such as AWS Kinesis, Kafka, or similar platforms.
Experience building and supporting batch data processing solutions using AWS Glue, Spark, or similar technologies.
Strong SQL and data transformation capabilities.
Experience with AWS services including Lambda, S3, DynamoDB, CloudWatch, SQS, SNS, API Gateway, and IAM.
Strong understanding of AWS networking, security, and access management.
Experience working with relational and NoSQL databases, including RDS, Redshift, DynamoDB, MongoDB, or similar technologies.
Experience implementing workflow orchestration using Apache Airflow (MWAA).
Ability to develop and maintain complex Airflow DAGs and automated workflows.
Strong understanding of monitoring, observability, alerting, and operational support.
Experience implementing data quality, logging, tracing, and performance monitoring solutions.
Familiarity with machine learning, AI, or generative AI tooling is advantageous.
Strong problem-solving, troubleshooting, and stakeholder engagement skills.
Experience working within Agile delivery environments.

Why Join Us?

Work on modern cloud-native data and analytics platforms.
Deliver high-impact solutions supporting advanced analytics, AI, and machine learning initiatives.
Collaborate with experienced engineers, architects, and data specialists.
Join a consulting culture focused on innovation, engineering excellence, and continuous improvement.
Benefit from strong career growth opportunities and exposure to leading AWS data technologies.

Quick Apply

Refine Your Search

machine learning engineer / data scientist jobs

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