At L'Oréal, our ambition is to become the #1 BeautyTech company, meaning inventing the beauty of the future while becoming the company of the future. As part of our Digital Transformation roadmap, we are designing and implementing the next generation of advanced and flexible tech products to enable business growth with the most efficient capabilities.
The individual in this role must demonstrate creatively, foresight and mature judgment as they anticipate and solve complex business problems by building data pipelines on cloud.
The position is challenged to identify problems quickly and correctly which otherwise elude. Projects typically would include multiple data application solutions, multiple digital technologies across various architectures. The person in the role will solve the problems with the best course of action within the departmental guidelines from existing solutions and works independently.
The individual communicates for needed investments and architectural changes or business needs is critical to ensure solutions can be created to meet the strategic business capability needs.
● Understand business priorities and success measures to design and implement the right data solutions.
● Have experience in data engineering fundamentals and displays eminence in modern data architectures across the organization.
● Support architecture design and implement end-to-end modern data platforms in support of analytics use cases.
● Build data applications based on design standards, design patterns and test procedures that support scalable data products.
● Collaborate with business stakeholders, IT product managers, data architects, ETL developers, engineers, BI developers/data scientists, and information designers to identify and define required data structures, formats, pipelines, metadata, and workload orchestration capabilities.
● Create, extract, transform, and load (ETLs/ELTs) and reporting systems for new data using distributed data systems.
● Maintain data pipelines by using DevOps techniques and build tools to reduce occurrences of errors and sustain high availability of the data application.
● Develop a proof-of-concept prototype with fast iteration and experimentation.
● Maintain technical skills and knowledge of market trends and competitive insights; collaborate and share with the technical community.
● Familiarity with Google Cloud platform (Big Query, Composer, Pub sub. Etc..) and Azure