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.

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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.

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Key Responsibilities

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

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Technical Skills

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- Solid hands-on experience in Python development.
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- Strong programming experience in Java.
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- Advanced SQL skills with experience in data extraction, transformation, and optimization.
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- Experience working with XML-based data structures and integrations.
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- Strong experience with AWS services relevant to data engineering.
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- Experience building and supporting ETL/Data Integration solutions.
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- Experience with secure file transfers including SFTP.
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- Knowledge of data validation, reconciliation, and quality controls.
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- Experience deploying solutions across non-production and production environments.
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- Understanding of data security, governance, and PII protection.
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- ETL/ELT design and development.
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- Data transformation and mapping.
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- File-based integrations.
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- Error handling and monitoring.
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- Experience with AI-assisted development tools such as:
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- Amazon Q
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- Similar AI engineering tools
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- Experience working within Agile delivery environments.
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- Exposure to CI/CD pipelines and DevOps practices.
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- Knowledge of enterprise integration patterns and cloud-native architectures.
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- Experience with data migration and system integration projects.
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Personal Attributes

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

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- 5+ years of experience in Data Engineering, ETL Development, or Data Integration.
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- Proven experience working with sensitive and regulated data sets.
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📌 Data Engineer (ETL & Data Integration) (Victoria)
🏢 Synechron
📍 Victoria