Data Platform Engineer - AWS & SageMaker

Roy Morgan Research; Melbourne; On-site; AUD 120,000 - 150,000; Full time

Benefits offered by this job

Vibrant work culture

Competitive salary package

Company social events

EAP service

MYKI pass discounts

Job summary

Roy Morgan is seeking a Data Engineer to join the Data Engineering team, building a scalable data platform on AWS SageMaker Unified Studio. You’ll enable data science and analytics users with governed, self-service access, while setting standards for Redshift and data storage.

The role emphasizes designing data pipelines, cubes for analytics, and modernizing legacy pipelines with security, governance and observability from day one.

Qualifications

• 3-5+ years' experience in Data Engineering or similar role, preferably in big data or market research.
• Strong data pipeline design, ETL/ELT, and data modelling for lake/warehouse.
• Python and SQL programming skills; R a plus.
• Hands-on with AWS data services: Redshift, Glue, S3, Lambda, Fargate, Lake Formation, EMR, SageMaker.

Responsibilities

• Build data platform on SageMaker Unified Studio for governed self-service access.
• Set and apply Redshift storage standards, schemas, partitioning, performance.
• Design and maintain OLAP/semantic cubes for analytics.
• Develop data APIs and file-based data access patterns.
• Design and build data pipelines (ingestion, ETL/ELT, transformation).
• Develop data lake/warehouse with suitable engines for performance.
• Move legacy batch pipelines to modern cloud platforms.
• Incorporate data quality, lineage, observability, security and governance.

Skills

Data engineering

Big data

Python

SQL

AWS

Redshift

SageMaker

ETL/ELT

Data modelling

OLAP

CI/CD

Data governance

REST/JSON

Security/compliance

Education

Bachelor's degree in IT/Data Science

Tools

Redshift

Glue

S3

Lambda

Fargate

Lake Formation

EMR

SageMaker Unified Studio

Job description

Roy Morgan is seeking a Data Engineer to join the Data Engineering team, building a scalable data platform on AWS SageMaker Unified Studio. You’ll enable data science and analytics users with governed, self-service access, while setting standards for Redshift and data storage.

The role emphasizes designing data pipelines, cubes for analytics, and modernizing legacy pipelines with security, governance and observability from day one.