Data Engineer

Paxus; City of Melbourne; On-site; AUD 124,000 - 193,000; Full time

Job summary

Paxus in Melbourne is seeking an experienced Data Engineer to design and operate scalable ETL/ELT pipelines. You will work with Informatica, BigQuery, SQL and Python to build robust data workflows across on-prem and cloud.

The role focuses on performance optimization, cost control and reliable data delivery. Applicants should have 4-7 years in data engineering, strong knowledge of Informatica and Google BigQuery, and the ability to document processes and collaborate with analytics teams.

Qualifications

• 4-7 years hands-on data engineering experience with production pipelines.
• Strong Informatica development, scheduling and monitoring skills.
• Proven BigQuery design, datasets, partitioning and performance tuning.
• Advanced SQL skills including complex joins and window functions.
• Python for data processing, automation and utilities.
• Experience with cloud data integration and hybrid on-prem/cloud setups.
• Ability to document mappings, runbooks and diagrams.

Responsibilities

• Build and maintain scalable ETL/ELT workflows using Informatica (mappings, workflows, scheduling and monitoring).
• Manage BigQuery datasets and tables, including partitioning and clustering for large-scale analytics.
• Write and optimise advanced SQL to improve performance and reduce compute cost.
• Develop Python scripts for file parsing, orchestration and integration with cloud APIs.
• Automate operational routines using Unix shell scripting (file transfers, pre/post-load steps, batch sequencing).
• Schedule, monitor and troubleshoot integrated batch workflows across on-prem and cloud schedulers.
• Implement robust data validation, error handling and logging to improve data quality and reliability.
• Diagnose and resolve bottlenecks across Informatica, BigQuery SQL and scripting components.
• Maintain technical documentation (mapping specs, runbooks, diagrams) and collaborate with analysts/testing/business stakeholders.

Skills

Informatica

BigQuery

SQL

Python

ETL pipelines

Data workflows

Education

Bachelor's degree in Computer Science / IT / Data Eng

Tools

Informatica

Google BigQuery

Unix shell

Python scripting

Job description

• Build and maintain scalable ETL/ELT workflows using Informatica (mappings, workflows, scheduling and monitoring)


• Manage BigQuery datasets and tables, including partitioning and clustering for large-scale analytics


• Write and optimise advanced SQL to improve performance and reduce compute cost


• Develop Python scripts for file parsing, orchestration and integration with cloud APIs


• Automate operational routines using Unix shell scripting (file transfers, pre/post-load steps, batch sequencing)


• Schedule, monitor and troubleshoot integrated batch workflows across on-prem and cloud schedulers


• Implement robust data validation, error handling and logging to improve data quality and reliability


• Diagnose and resolve bottlenecks across Informatica, BigQuery SQL and scripting components


• Maintain technical documentation (mapping specs, runbooks, diagrams) and collaborate with analysts/testing/business stakeholders

Location: Melbourne
Contract: 12 month

Responsibilities

• Build and maintain scalable ETL/ELT workflows using Informatica (mappings, workflows, scheduling and monitoring)


• Manage BigQuery datasets and tables, including partitioning and clustering for large-scale analytics


• Write and optimise advanced SQL to improve performance and reduce compute cost


• Develop Python scripts for file parsing, orchestration and integration with cloud APIs


• Automate operational routines using Unix shell scripting (file transfers, pre/post-load steps, batch sequencing)


• Schedule, monitor and troubleshoot integrated batch workflows across on-prem and cloud schedulers


• Implement robust data validation, error handling and logging to improve data quality and reliability


• Diagnose and resolve bottlenecks across Informatica, BigQuery SQL and scripting components


• Maintain technical documentation (mapping specs, runbooks, diagrams) and collaborate with analysts/testing/business stakeholders

Requirements

• 4-7 years' hands-on data engineering experience building and supporting production data pipelines


• Strong Informatica experience (development, scheduling, monitoring, troubleshooting)


• Proven Google BigQuery capability (table design, dataset management, partitioning/clustering, performance optimisation)


• Advanced SQL skills (complex joins, window functions, tuning, validation routines)


• Python proficiency for data processing, automation and reusable utilities


• Strong understanding of operational monitoring, reconciliation, logging and batch workload support


• Demonstrated ability to troubleshoot end-to-end data pipeline issues across tools and scripts


• Experience producing and maintaining technical documentation and working in delivery teams

Desirables

• Unix shell scripting for orchestration/automation in data pipeline operations


• Experience supporting cloud migration or hybrid integration (moving legacy on-prem data into cloud platforms)


• Familiarity with Agile delivery, version control and release processes across distributed teams


• Relevant degree (Computer Science / IT / Data Engineering or similar) and/or cloud/data/Informatica certifications

Paxus values diversity and welcomes applications from Indigenous Australians, people from diverse cultural and linguistic backgrounds and people living with a disability. If you require an adjustment to the recruitment process, including the application form in an alternate format, please contact me on the above contact details.