In-Demand Risk governance & reporting analyst Jobs in Parramatta, Nsw

Data Engineer
Perfection Fresh Australia —Homebush NSW
- Full-time
- ERP systems
- SQL
- APIs
Quick Apply
3d
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Mission Australia —Sydney NSW
- From $115,000 a year
- Full-time
- Data analysis skills
- Analysis skills
- No degree
- Work from home
2h

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Data Engineer

Perfection Fresh Australia -
Homebush NSW

Quick Apply

Job Details

Permanent | Full-time
3 days ago

Qualifications

CI/CD
Food production
Data modelling
Deployment
ERP systems
SQL
GitHub
APIs
Security
AI
Communication skills
Design patterns

Full Job Description

Introduction:
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.

Learn more about us and discover other exciting opportunities at www.perfection.com.au.

Description:
Key Responsibilities

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.

Skills and Experiences:
Essential Requirements

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.

Nice to Have

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.

Quick Apply

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