Job Description
Data Integration Engineer - Business In Scale Up!
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We are excited to bring to market a newly created role with a financial services client that is in scale-up mode after launching a new and innovative lending product for the benefit of the Australian consumer.
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Well-backed with capital from partners with a global presence, they are now looking to attract a highly motivated and forward thinking Data Integration Engineer, to work directly with the CTO in designing, building, managing, and optimising data pipelines and data flows across the organisation.
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They require an innovative Data Engineer with a background in automation and BI, to deliver operational efficiencies, meaningful insights and data assets across all areas of the business.
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Key responsibilities
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Contribute to data architecture design, ETL development, optimisation and building out data stores for reporting and insights us MS Fabric
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System integration & API management for connecting SaaS applications for financial data exchange
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Workflow orchestration through low-code process automation and AI for lending and risk management
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Automation of data movement and RPA engineering of manual tasks
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Data quality and security management
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To be considered for the role you will need to have a strong technical background in cloud data engineering, integration and automation tools:: MS Fabric, SQL, Power Platform (including Power Query, DAX, Power BI and Power Automate), Azure (including Azure Data Factory, Logic Apps and AI Builder), AWS (including Lambda, S3 and RDS/Aurora), and REST APIs.
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You will be empowered to run with your own decision making and work directly with the business on delivering recent and innovative data solutions from scratch.
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But most importantly, you will have excellent aptitude and want to be part of a supportive and forward thinking start-up culture, where you can celebrate in it's success and build your future career.
#J-*****-Ljbffr
📌 Data Integration Engineer - Business In Scale Up! (New South Wales)
🏢 T+O+M Executive
📍 New South Wales
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