Senior Data Platform Engineer - ETL & Leadership

Softtest Pays Pty

Melbourne

On-site

AUD 140,000 - 165,000

Full time

14 days+

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Job summary

Softtest Pays Pty is seeking an EL1 Data Acquisition Engineer to join a senior project stream for the NDIA data warehouse platform in Melbourne. The role involves hands-on development, guiding developers, and reviewing data designs to support rapid subject-area expansion.

You will lead design reviews, refine the data delivery framework, and own the end-to-end implementation from analysis to release. Collaboration with data consumers and IT teams will be essential to success.

Qualifications

  • Proven track record in data engineering, ETL and SQL development.
  • Experience leading data delivery, design reviews and release processes.
  • Strong collaboration with data consumers, testers and IT support teams.

Responsibilities

  • Provide technical leadership through design reviews and workshops.
  • Refine data delivery framework and integrate new data sources.
  • Own end-to-end data delivery from analysis to dictionary and release steps.
  • Promote coding standards, documentation and best practices.
  • Deliver knowledge transfer sessions and peer reviews on development and data modelling.
  • Prioritize work items and manage a work queue.
  • Analyze, size and document user requirements.
  • Develop and maintain SQL analytic and ETL code.
  • Update system documentation and collaborate with related teams.

Skills

Performance
Data
Steps
Project Delivery
Support
Database
ETL
Development
Collaboration
Analysis
Reviews
Workshops
Developers
Continuous Improvement
Integration
Documentation
Maintenance
Design
SQL
Training
Leadership

Job description

Softtest Pays Pty is seeking an EL1 Data Acquisition Engineer to join a senior project stream for the NDIA data warehouse platform in Melbourne. The role involves hands-on development, guiding developers, and reviewing data designs to support rapid subject-area expansion.

You will lead design reviews, refine the data delivery framework, and own the end-to-end implementation from analysis to release. Collaboration with data consumers and IT teams will be essential to success.

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