Qualifications

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You will need a collaborative delivery approach to be successful

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We prefer to use Agile but choose the appropriate approach for the project

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So, experience of a variety of delivery management methodologies would come in useful

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Experience with & knowledge in a broad base of data tools, ETL frameworks, monitoring and data technologies, for example our stack includes: SAP HANA, SAP MDG, PowerBI, Qlik Sense, Qlik Replicate, EMR, Hudi, Collibra, Snowflake, DBT, DataKitchen, AWS Kinesis

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Experience of visualisation technologies (we are focused on Power BI and Qlik Sense),

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Knowledge of Data Mesh and Data Product, in particular, experience with delivering and managing data products

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Knowledge of data architectures, design including dimensional modelling

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Knowledge of cloud-based data management services: AWS, or equivalent

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Advanced SQL skills

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Experience of building scalable high availability analytics solutions

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Continuous integration and continuous development

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Experience of data analysis, such as: profiling, investigating, interpreting and documenting data structures

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Experience in identifying and delivering overall data engineering activities as part of design, built, execution for many initiatives

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Knowledge of SAP and SAP analytics platforms

Responsibilities

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This is being achieved through the creation of a distributed data architecture, management of our data and data products will sit at the heart of this

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As a Analytics and Engineering Tech Lead, you will support solution development, provide technical leadership, and take responsibility for delivery across many initiatives

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You will guide and contribute to engineering teams accountable for harvesting, storing, quality checking, transforming, and visualising Operations data, build out reusable data products, which users from Operations units can self-service for analytics and AI/ML workflows

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You will also own the engineering standard, processes, engineering roadmap, and work with solution architecture to create a technology roadmap

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You will be accountable for the efficient, secure and complaint engineering and running of data products

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You will also work closely with the Enterprise Data & AI teams to demonstrate central Enterprise Data Platforms for Data Cataloguing, Master Data Management and Reference Data Management