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 contemporary 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.
#J-*****-Ljbffr

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