The Staff Analytics Engineer, Databricks (R5493) role at Shield AI is a pivotal position that entails owning the Gold layer and enterprise semantic layer of the Databricks lakehouse, where clean and governed Silver-layer data becomes trusted, business-ready models, KPIs, and semantic assets. This role matters because it translates approved business definitions into auditable transformation logic and durable analytics models that can be used consistently across multiple domains, driving business growth and informed decision-making. As a Staff Analytics Engineer, you contribute to the company's success by developing and maintaining the core analytics infrastructure, ensuring data quality, and enabling data-driven insights. The impact and scope of this position are significant, as it spans multiple domains and requires collaboration with cross-functional teams. With this role, you have the opportunity to grow and advance your career, taking on new challenges and expanding your skill set in a dynamic and innovative environment.

As a Staff Analytics Engineer, your key responsibilities include designing, developing, and maintaining large-scale analytics systems using Delta Lake, Apache Spark SQL, and other big data technologies. Your day-to-day activities involve working with stakeholders to understand business requirements, developing and refining analytics models, and ensuring data quality and governance. Some of your main responsibilities include:

• Developing and maintaining the Gold layer and enterprise semantic layer of the Databricks lakehouse


• Creating and managing KPI dashboards and reports to inform business decisions


• Collaborating with data engineers to design and implement data pipelines and architectures


• Working with business stakeholders to understand requirements and develop analytics solutions


• Ensuring data quality, security, and compliance with industry standards


• Staying up-to-date with industry trends and emerging technologies, such as artificial intelligence and machine learning. You will be working remotely and reporting to the engineering leadership team, collaborating with a talented team of engineers, data scientists, and analysts to drive business success. To be successful in this role, you need to have strong technical skills in analytics, data engineering, and software