About the Role

We are seeking 5 experienced Data Engineers to design, build, deploy, and support enterprise-grade ETL solutions that integrate data from SQL databases and CSV-based source systems. The role involves transforming data into consumer-specific CSV interfaces and securely delivering outputs via SFTP or similar mechanisms.

The ideal candidates will be self-driven engineers with strong data engineering expertise, capable of designing scalable solutions, implementing appropriate controls for sensitive data, and managing deployments across non-production and production environments.

Key Responsibilities

- Design, develop, and maintain ETL pipelines for ingesting and transforming data from:
- SQL Databases
- CSV files
- Enterprise data sources
- Develop robust data transformation frameworks to generate consumer-specific CSV interfaces.
- Implement secure file delivery mechanisms including SFTP and related protocols.
- Build scalable, reusable, and maintainable data processing solutions using Python and Java.
- Design and implement data validation, reconciliation, monitoring, and exception handling processes.
- Deploy and promote ETL solutions across Development, UAT, and Production environments following established governance and release processes.
- Ensure compliance with data security, privacy, and governance requirements, particularly around Personally Identifiable Information (PII).
- Collaborate with business stakeholders, architects, and consumers to understand requirements and propose fit-for-purpose technical designs.
- Troubleshoot production issues and provide operational support for critical data integrations.
- Leverage modern AI-assisted development tools such as Claude Code and similar platforms to improve engineering productivity and solution quality.

Mandatory Skills & Experience

Technical Skills

- Robust hands-on experience in Python development.




- Strong programming experience in Java.
- Advanced SQL skills with experience in data extraction, transformation, and optimization.
- Experience working with XML-based data structures and integrations.
- Strong experience with AWS services relevant to data engineering.
- Experience building and supporting ETL/Data Integration solutions.
- Experience with secure file transfers including SFTP.
- Knowledge of data validation, reconciliation, and quality controls.
- Experience deploying solutions across non-production and production environments.
- Understanding of data security, governance, and PII protection.

Data Engineering Expertise

- ETL/ELT design and development.
- Data transformation and mapping.
- File-based integrations.
- Batch data processing.
- Data ingestion frameworks.
- Error handling and monitoring.

Desirable Skills

- Experience with AI-assisted development tools such as:
- Claude Code
- GitHub Copilot
- Amazon Q
- Similar AI engineering tools
- Experience working within Agile delivery environments.
- Exposure to CI/CD pipelines and DevOps practices.
- Knowledge of enterprise integration patterns and cloud-native architectures.
- Experience with data migration and system integration projects.

Personal Attributes

- Self-starter with strong ownership and accountability.
- Ability to translate business requirements into effective technical solutions.
- Strong problem-solving and analytical skills.
- Excellent communication and stakeholder management abilities.
- Ability to work independently in a fast-paced environment.
- Strong focus on quality, security, and operational excellence.

Preferred Experience

- 5+ years of experience in Data Engineering, ETL Development, or Data Integration.
- Experience designing end-to-end data integration solutions in enterprise environments.
- Proven experience working with sensitive and regulated data sets.

📌 Data Engineer (ETL & Data Integration) (Melbourne)
🏢 Synechron
📍 Melbourne