Data Eng II (PnD), IT PnD Data Engineering

Would you like to be the go-to Data Engineer for a team that constantly learns new domains, tools and data sources to identify best practices from across Amazon’s broad offerings and propagate them globally? IT PnD Data Engineering team is looking for a Data Engineer to join the team to design, manage, and continuously enhance our data and analytics infrastructure, with process automation/improvements, developing automated reporting solutions/tools, and improving the ability of the IT Services organization to process, analyse, access and consume accurate and timely data. As a Data Engineer you will be working in one of the largest cloud-based data lakes. You should have experience in the design, creation, management, and business use of extremely large datasets. You should have excellent business and communication skills to be able to work with business owners to develop and define key business questions, and build data sets that answer those questions. You should be able to architect highly efficient data and reporting structures, making a trade-off between scalability, performance and user functionality needs, using expert knowledge in software development technologies. You should be able to lead design reviews and offer feedback on design, integration, performance and scalability issues. Serve as an authority in the area of technical and domain expertise and mentor, develop, and train data engineers. Key job responsibilities In this role you will work with a team in building near real time data ingestion, calculation engines, and reporting solutions for IT Services organization. The role requires someone who loves data, understands enterprise information systems, has a strong business sense, and can collaborate with multiple teams to put these skills into action. The ideal candidate thrives in a fast-paced environment, relishes working with ambiguity, big data, and enjoys the challenges of highly complex business context. This role requires an individual with a strong data modelling background, deep knowledge of cloud infrastructure, optimizing data for business intelligence solutions, and the ability to quickly learn, adapt and work with a variety of technologies.