Data Engineer
Why This Role Stands Out
Leverage your skills to build robust data solutions on the Microsoft Fabric platform, driving innovation within a leading Australian fresh produce company with a strong reputation for growth. This hybrid role offers an excellent opportunity for a mid-senior Data Engineer to develop scalable frameworks and collaborate with cross-functional teams, making a tangible impact on business-critical data initiatives.
Quick Overview
Job Description
Our mission is to make fresh fruits and vegetables a more loved and essential part of everyone's life.
Perfection Fresh is one of Australia's largest privately owned fresh produce companies that's been on an exciting journey of innovation and growth since 1978.
We're an Australian-based business that grows, packs, and markets fresh produce both domestically and internationally. You'll recognize our produce - Qukes , Broccolini , Calypso mangoes, and more.
Our history 45-year history is one of continuous progress. We're the market leader in our field and we've been listed on the Australian Financial Review's top 100 private companies in Australia.
We employ more than 2,000 people across a portfolio of farming sites, high-tech production facilities, research, corporate offices, and national logistics operations.
- Build, develop and maintain high-quality data pipelines, lakehouse/warehouse structures, notebooks, dataflows and semantic models on the Microsoft Fabric platform.
- Ingest, transform and model data from a range of enterprise sources, including ERP systems such as Business Central, APIs, databases, files, IoT platforms, cloud systems and operational applications.
- Apply medallion architecture principles across bronze, silver and gold data layers to ensure data is structured, reliable, reusable and fit for reporting, analytics and AI/ML use cases.
- Implement data quality controls, validation rules, reconciliation processes, audit logging and monitoring to ensure downstream reporting and analytics are accurate and reliable.
- Work closely with the Data Engineering Lead, Data Management Lead, Data Product Owners, Business Analysts, software developers and ERP teams to deliver business-critical data use cases.
- Develop scalable, reusable data engineering frameworks (incremental loads, parameterised pipelines, reusable ingestion patterns) and follow good engineering practices, including source control, deployment discipline, environment-specific configuration, documentation and CI/CD for Microsoft Fabric artefacts.
- Support data governance, security, lineage, metadata management and catalogue practices, including alignment with Microsoft Purview where applicable.
- Minimum 3 years' hands-on experience in data engineering, building data solutions on modern cloud platforms (ideally Microsoft data technologies), including lakehouse/warehouse services, data pipelines, notebooks, cloud storage and semantic or reporting models.
- Strong SQL skills, with experience in data modelling, stored procedures, query optimisation, performance tuning and warehouse/lakehouse design patterns.
- Experience with source control and structured deployment practices, preferably including GitHub, CI/CD and environment-specific configuration.
- Understanding of data governance, security, lineage, metadata management and catalogue practices.
- Strong communication and collaboration skills, with the ability to work across technical teams, business analysts and business stakeholders, explaining technical issues, delivery progress, risks and data quality findings in clear business language.
- Microsoft Fabric experience, including OneLake, Lakehouse, Warehouse, Pipelines, Dataflows, Notebooks and semantic models.
- Experience working in agriculture, food production, FMCG, logistics, supply chain or other operationally complex industries.
- Exposure to Business Central, workforce management systems, farm/production systems, IoT platforms or operational data sources.
- Understanding of AI/ML data preparation, feature engineering or data engineering patterns that support advanced analytics and AI-enabled use cases.
- Experience with real-time or near-real-time data ingestion and stream processing.
Skills
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