Recruiting candidates for Digital Data Lead

Job Description

*onsemi (Nasdaq: ON) is driving disruptive innovations to help build a better future. With a focus on automotive and industrial end-markets, the company is accelerating change in megatrends such as vehicle electrification and safety, sustainable energy grids, industrial automation, and 5G and cloud infrastructure. With a highly differentiated and innovative product portfolio, onsemi creates intelligent power and sensing technologies that solve the world s most complex challenges and leads the way in creating a safer, cleaner, and smarter world.ResponsibilitiesCreating value from business-driven data and analytics initiatives.The most important task for the Digital Data Lead is to support the business and other stakeholders in their data-driven objectives. This means they will support the business during various stages: In the inspiration phase, help the business in identifying the right use cases and support prioritization based on feasibility and value In the ideation phase, help with the prototyping and associated business case (estimated cost and benefits). Create business case analysis (BCA) and take it through toll gate process for approval. During the implementation phase, ensure product is delivered to the specs (both business and technical requirements) measure the adoption, and share with the rest of the organization where applicable.Raise the level of data literacy in the organization. Raising the business literacy of the D&A teams Education and coaching of the business to become more data-savvy Facilitating data-centric business thinking Ensuring that data and analytical solutions comply with relevant regulations and standards Improving data quality and securing trust in dataHelps uncover and translate business requirements and needs. This translation needs to be done in such a way that the specialists in the D&A team can understand. This requires an understanding of the business objectives, goals, and domain expertise, as well as D&A concepts, methods, and techniques. It requires strong soft skills with a focus on communication. The Digital Data Lead can also work with C-level executives/the board of directors to support their data-driven vision, strategy and operating models. Because of the experience and set of skills (soft, data and analytics, domain and technology) required to be successful, the role of the Digital Data Lead is a senior role. The Digital Data Lead should spend most of their time (up to 80%) with the business., *Soft Skills The Digital Data Lead needs to be highly proficient in soft skills: Communication - convey information to diverse audiences in a way that is easily understood and actionable. Facilitation - host sessions to elicit ideas from others, understand their issues and encourage group participation. Creative thinking - frame new concepts that spur use case ideation for business participants and brainstorming with business users about future product and services. Teamwork - work with business domain teams as well as D&A teams and IT staff. Collaboration - foster group problem solving and solution creation with business and technical team members. Relationship management - create relationships and building trust with internal and external stakeholders quickly. Storytelling - create a consistent storyline for better understanding and raising literacy. Influencing - assert ideas and persuade others to gain support across an organization or to adopt new behaviors. Presentation - comfortable with public speaking and the ability to creatively and concisely express ideas to business and technical audiences.Data and Analytics Skills The Digital Data Lead needs to have a good understanding of the concepts, methods and techniques used: Analytics - diagnostic, descriptive, predictive, and prescriptive. Data management - data integration (ETL) or metadata. Data architecture - the difference between data warehouse, data lake or data hub. Data structures - structured, semi structured, and unstructured data. Data governance - MDM, data quality and data stewardship practices. Statistical skills - understanding the difference between correlation and causation.Domain Skills The Digital Data Lead needs to have a good understanding of the business process and associated data: Business acumen - understand business concepts, practices, and business domain language to engage in problem-solving sessions and discuss business issues in stakeholder language. Business process transformation - the ability to understand how D&A can help redesign the way work is done. Business data, for example the structure, ownership and use within an organization.Other Skills The Digital Data Lead needs to have a basic understanding of generic methods and techniques, such as: Project management capabilities, for example understanding of project management concepts to organize their own work and the ability to collaborate with project managers to align business expectations with the D&A team delivery capabilities. For this, the role can collaborate with project managers. Business case development, for example to help develop support for experimenting with selected use cases or measuring the impact/business value created. For this, the role can collaborate with business analysts. UX/design, for example by creating products and visualizations that are easy to work with and support the activities required by the end users. For this, the role can collaborate with the design team.Technology Skills The Digital Data Lead needs to have a basic understanding of the principles, methods and techniques of D&A decoupled from the tools and technologies in the D&A team: Programming languages like SQL, Python. Data integration patterns like CDC, Streaming, REST API integration. Analytics and business intelligence tools like QlikView and Tableau.Proficiency Level: Soft Skills Practitioner/ExpertD&A Skills Practitioner/ExpertDomain Skills Familiarity/ PractitionerOther Skills Basic/Familiarity#LI-KH1#LI-Onsite

Keyskills :
business case developmentbusiness intelligence toolsbusiness case analysissoft skillsdata qualitycase analysisdata managementdata structures