Key Responsibilities

• Data Architecture & Automation
• Modern Data Architecture: Build out and refine our next-generation Bedrock Platform, utilising a Medallion Data Architecture (Bronze, Silver, Gold layers) to structure scalable data models.
• Transparent Lineage & Layered Testing: Establish transparent data lineage across all pipelines and design automated test suites at each layer of the data architecture to ensure end-to-end data quality.
• Platform Automation: Automate operational tasks and build resilient data infrastructure to eliminate repetitive break-fix work and prevent recurring issues.
• SDLC Practices: Apply modern software development practices (git version control, modular code, pull requests, continuous testing) to data pipelines.
• Legacy Maintenance & Migration (6 to 12 Months)
• Balancing Priorities: Successfully balance ongoing maintenance and bug fixes on the Legacy Platform with dedicated build time for the new architecture.
• Legacy Code Wrangling: Dive into less structured legacy SQL logic and Alteryx ETL workflows, unpicking complex data pipelines to troubleshoot discrepancies or alter logic.
• Pragmatic Prioritisation: Comfortably navigate imperfect legacy code, identifying and executing on low-hanging fruit to deliver immediate reliability wins without getting bogged down.
• Platform Migration: Systematically refactor legacy datasets and logic into the Bedrock Platform as customers are transitioned across.
• Data Operations & Quality
• Ensure high data quality and accuracy across incoming raw data, intermediate transformations, and outgoing analytical models.
• Trace and resolve data anomalies quickly across collection, transformation, and delivery stages.
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Requirements

Eligibility

• Residing in Sydney, Australia with full Australian working rights (candidates not already residing in Sydney, Australia; on temporary / part-time work visas; or requiring sponsorship will not be considered for this role)
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Essential Skills

• SQL Expertise: 2+ years of deep experience writing complex, performant, and scalable SQL (Snowflake experience is highly regarded).
• Legacy SQL Troubleshooting: Demonstrated ability to interpret messy or unstructured legacy SQL code, understand existing workflows, and refactor them safely.
• Pipeline Architecture & Testing: Experience architecting data pipelines, implementing medallion architecture patterns, creating data lineage, and designing test suites across each layer.
• Pragmatic Mindset: Comfort working in a fast-paced, lean team with a knack for balancing legacy maintenance against new feature build, picking off low-hanging fruit efficiently.
• Data Transformation: High proficiency in data manipulation and cleansing techniques (joins, transposes, crosstabs, regex, aggregations).
• Communication: Clear written and verbal communication to explain data logic, lineage, and system trade-offs to internal stakeholders.
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Highly Desirable (Or Demonstrated Willingness to Learn)

• dbt & Semantic Layers: Experience using dbt (or a similar tool) to build scalable data architectures, transparent lineage, and semantic layers.
• Data SDLC: Commercial experience using software engineering principles like Git, branching, and automated testing for data workflows.
• Note: If you do not have direct dbt or formal Git/SDLC experience in data, you must demonstrate strong technical aptitude and a willingness to learn quickly.
• ETL Tooling: Experience with Alteryx or similar visual ETL tools is a strong plus (though not a strict necessity).