Lead- Data Engineering

You will lead a team and build systems that solve complex business problems at scale. You will work closely with product managers to understand customer needs and translate those into technical requirements. Furthermore, you will build and maintain scalable data management and serving infrastructure on the cloud, managing terabytes of data and integrating cost effectively. Your role will involve building, leading, and managing a rockstar team, as well as taking end-to-end ownership of the engineering process. You will be responsible for designing a comprehensive target data architecture vision in collaboration with product, design, development, and NatCo teams to plan the transition towards the target vision. Your responsibilities also include implementing architecture concepts in product development and services, consulting and engaging with engineering teams to solve problems at their root cause, and creating deliverables that provide exceptional clarity and connections to business objectives. In the realm of data specialization, you are expected to possess comprehensive and expert knowledge with more than 5 years of experience in Data Management and Data Architectures (DWH, Spark, Lakehouse) along with an overall experience of 7-10 years. You should have a deep understanding of concepts and principles related to both Batch and Streaming data, API/Microservices architectures, Data warehouses, and Mesh Architectures. Strong expertise in Big Data Applications, Architecture best practices, and experience with legacy Data Warehouses and Big Data platforms are essential. Additionally, you should have exposure and understanding of decision engine concepts and the implementation of MLOps within an enterprise. Your experience in software engineering and programming languages like Java and Scala will be valuable. Proven track record of working with globally federated IT teams is expected, along with a sound understanding of the challenges involved and the ability to bring teams and people together to deliver a shared outcome. Data Modelling experience, including Information framework SID and Data Vault 2.0, is a plus. In terms of security and regulatory rigor, you should be experienced in implementing solutions that protect sensitive and regulated Customer data. Your expertise should cover Security Architecture concepts such as identity and access management, network isolation, transport protection, cloud security specifics, encryption & key management, and data privacy treatment techniques. Strong intrapersonal skills are crucial for facilitating difficult discussions within the team or with diverse senior stakeholders. You should be resilient and able to adapt yourself and teams to changing environments and business situations. Extensive experience in multicultural environments and fast-moving, highly competitive markets is desired.,