Data Engineer (ETL & Data Integration)

Synechron; City of Melbourne; On-site; AUD 120,000 - 180,000; Full time

Job summary

Synechron in Australia seeks 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 focuses on transforming data into consumer-specific CSV interfaces and securely delivering outputs via SFTP or similar mechanisms.

The ideal candidates are self-driven engineers with robust data engineering expertise, capable of designing scalable solutions, implementing controls for sensitive

Qualifications

• Strong hands-on experience in Python development.
• Java programming proficiency with data integration focus.
• Advanced SQL skills including data extraction and transformation.
• Experience with XML-based data structures and integrations.
• Proficiency with AWS services relevant to data engineering.
• Experience building ETL/Data Integration solutions.
• Familiarity with secure file transfers (SFTP).

Responsibilities

• Design, develop, and maintain ETL pipelines for ingesting data from SQL Databases and CSV files.
• Build robust data transformation frameworks to generate consumer-specific CSV interfaces.
• Implement secure file delivery mechanisms including SFTP and related protocols.
• Deploy ETL solutions across Development, UAT, and Production environments.
• Ensure data security, privacy, and governance, especially PII protection.
• Collaborate with stakeholders to translate requirements into technical designs.
• Troubleshoot production issues and provide operational support for data integrations.
• Leverage AI-assisted development tools to improve productivity and quality.

Skills

Python

Java

SQL

XML

AWS

ETL/ELT

SFTP

Data validation

CI/CD

Data migration

Job description

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
• 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

• Strong 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.
• ETL/ELT design and development.
• Data transformation and mapping.
• File-based integrations.
• Error handling and monitoring.
• Experience with AI-assisted development tools such as:
• 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.
• Proven experience working with sensitive and regulated data sets.