The Design for Scale (DfS) Business Intelligence Engineer will build and manage a novel Business Analytics and Intelligence mechanism to inform the business on product impact throughout the Product Development Process. The DfS Business Intelligence & Analytics team’s charter is to inform the executive, technical, operations, and corporate stakeholders of key business performance and financial indicators with a high degree of confidence and fidelity via rigorous systems and statistical analysis. These indicators will inform dynamic models that will be true to the current product testing and deployment scope, traceable to product requirements, giving a concise and live view of the product’s Financial, Supply Chain, Manufacturing, Maintenance & Reliability, Widget, Process, and Scaled Deployment risks in a form. This Form will allow for efficient and deep approval reviews using key business metrics (IRR/NPV/TCO/COPQ/Enterprise Risk) at the top level, while giving the ability to drill deep into the metric inputs in a live and dynamic setting (MTBI/MTBF/MTTR/DPMO/TPH/Etc) down to the individual machine PLC.
The DfS BIE is a high visibility position and will regularly interface with Senior tech and non-tech stakeholders and leaders. Candidate should be comfortable with ambiguity, capable of working in a fast-paced environment, continuously improving technical skills to meet business needs, possess attention to detail and be able to collaborate with customers to understand and transform business problems into requirements and deliverables.
The ideal candidate will possess the expertise and knowledge of the business and its technologies to drive deep, data based discussions with customers. The candidate will anticipate and influence future requirements to continuously Raise the Bar in our products’ data pipelines and models. The candidate should have a frugal and lean prospective to their work, leveraging existing infrastructure and eliminating waste when observed. The BIE’s outputs will be statistically accurate, back-testable, traceable, and actionable. A high degree of business acumen and judgement is needed as the BIE will be expected to advise executives through ambiguous events in pursuit of the best business decision. The BIE will manage several large scale projects at different phases, so a high degree of program organization is required.
The BIE will understand capabilities and limitations of the systems they work with (e.g. cluster size, concurrent users, data classification). They are able to explain these limitations to technical and non-technical audiences, helping them understand what’s currently possible and which efforts need a technology investment (e.g., data pipeline doesn’t exist, report needs additional functionality, etc.). Code submissions and analytics approach to work must be exemplary. BI solutions are inventive, robust, scalable, extensible, and easy for others to maintain and build upon.
The BIE will own team infrastructure, providing a system-wide view and design guidance. They will drive BI engineering best practices (e.g. Operational Excellence, code reviews, syntax and naming convention, metric definitions, alarms) and set standards across the cross functional teams. The BIE will build consensus; when confronted with discordant views, and will leverage data and statistics to find the best path forward and advise the stakeholder group.
Key job responsibilities
Key job responsibilities
- Design, develop and maintain scaled, automated, customer-centric systems, reports, dashboards, etc.
- Partner with Executive/Engineering/Operations/Business/Corporate Teams/Finance /Machine Learning (ML) teams to consult, develop and implement key performance indicators (KPI’s), automated reporting/process solutions and data infrastructure improvements to meet business needs.
- Develop the PLC to Dashboard automation of pipelines for Machine Performance and Health metrics.
- Apply analytic skill to extract meaningful insights and learnings from large and complicated data sets, culminating in extremely accurate financial modeling and forecasts.
-Reporting of results Exucutive groups via Exit Gate Reviews, QBR/MBR, OP1/2, etc.
- Serve as liaison with Business and technical teams to achieve project objectives, requiring data gathering, problem solving, modeling, and communication of insights and recommendations.
