TAL Australia5 followers44 jobs

Cloud Data Engineer

Mid levelFull-timeOfficeSydney NSW, AustraliaPosted 6 days agoVerified 6 days ago
Pending fitX of Y criteria met

About the job

The Data Engineer job at TAL is all about enabling data-driven capabilities by designing, building, and maintaining robust data pipelines. This role is crucial for ensuring that data is reliable, scalable, and accessible, supporting various business needs. The team thrives on collaboration, innovation, and a shared commitment to continuous improvement, making it an exciting opportunity to grow and contribute in a dynamic environment.

Meet the team

About the company

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You'll be responsible for

🚀

Designing and building data pipelines

Design, build and maintain robust batch and near real-time data pipelines that ingest, transform and publish data for reporting, analytics, operational and AI-enabled use cases.
🔄

Maintaining data transformations

Build and maintain data transformations that prepare trusted, well-structured and reusable datasets for downstream consumption.
🤝

Collaborating with teams

Collaborate closely with architects, platform engineers, analysts, product owners and business stakeholders to shape practical and reusable solutions.

Key criteria

🔧

Data engineering fundamentals knowledge

Strong understanding of ETL, ELT, and data transformation processes.

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☁️

Cloud data platform experience

Hands-on knowledge of Azure, Microsoft Fabric, and Databricks.

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📊

SQL proficiency

Demonstrated experience writing complex SQL queries for data analysis.

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A meaningful career starts with a match

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5 criteria for this job
Data engineering fundamentals knowledge
Strong understanding of ETL, ELT, and data transformation processes.

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Cloud data platform experience
Hands-on knowledge of Azure, Microsoft Fabric, and Databricks.

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SQL proficiency
Demonstrated experience writing complex SQL queries for data analysis.

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Python and Spark skills
Experience with Python, Spark, or similar data engineering frameworks.

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Data quality assurance
Experience embedding validation logic and operational controls in data pipelines.

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