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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Strong 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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Solid 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