Descrição

Company Description

AUTODOC is the largest and fastest growing auto parts ecommerce platform in Europe.

Present across 27 countries with around 5,000 employees, AUTODOC generated revenue of over €1.3 billion in 2023, supplying more than 7.4 million active customers with its 5.8 million vehicle parts and accessories for car, truck, and motorcycle brands.

Curious minds, adventurous experts and tech-savvy professionals - one team, one billion euros revenue. Catch the ride!

Responsibilities

Job Description

• 1 Business Needs Analysis & Problem Identification
• Conduct in-depth analysis of business processes, challenges, and opportunities to identify where data products can provide value.
• Engage with stakeholders across departments to understand their pain points, operational inefficiencies, and strategic goals.
• Use techniques from BABOK, such as root cause analysis, process modeling, and stakeholder interviews, to define business needs before prescribing solutions.
• Challenge assumptions and explore alternative solutions that maximize business value.
• Proactively propose data-driven opportunities instead of waiting for stakeholders to define requirements.

• 2 Solution Generation & Data Product Strategy
• Work collaboratively with stakeholders and product teams to define problem statements, ideate solutions, and validate hypotheses.
• Leverage industry best practices, market research, and internal data to design innovative and scalable data products.
• Conduct feasibility assessments and cost-benefit analyses to determine the viability of potential solutions.
• Define data product vision, scope, and success criteria based on business needs and strategic alignment.

• 3 Requirements Management & Documentation (BABOK-aligned)
• Apply BABOK's requirement lifecycle management framework to ensure traceability, consistency, and alignment of requirements.
• Elicit requirements using structured techniques such as interviews, focus groups, prototyping, surveys, and document analysis.
• Develop and maintain structured Business Requirement Documents (BRD), Functional Requirement Specifications (FRS), and Product Requirement Documents (PRD).
• Categorize requirements into business, stakeholder, solution, functional, and non-functional categories to ensure clarity.
• Utilize use case modeling, process flow diagrams, and data flow diagrams to document and communicate requirements effectively.
• Ensure requirements are clear, testable, and adaptable to changing business needs.

• 4 Stakeholder Engagement & Collaboration
• Act as a trusted advisor to business stakeholders, helping them understand and articulate their data needs.
• Facilitate requirements workshops, brainstorming sessions, and design sprints to drive alignment.
• Manage stakeholder expectations and negotiate priorities to balance business goals and technical feasibility.
• Translate complex data concepts into clear, business-friendly language.
• Maintain ongoing communication with product managers, data engineers, analysts, and business users.

• 5 Agile & Product Development Lifecycle Management
• Work closely with product teams using Agile methodologies to ensure continuous delivery of valuable data products.
• Define and maintain the product backlog, ensuring well-structured epics, features, and user stories.
• Participate in sprint planning, backlog grooming, daily stand-ups, and retrospectives.
• Collaborate with engineering teams to ensure business requirements are translated into actionable technical deliverables.
• Conduct UAT (User Acceptance Testing) and validate that delivered solutions meet business needs.

• 6 Data-Driven Decision Making & Performance Evaluation
• Define Key Performance Indicators (KPIs) and Objectives & Key Results (OKRs) to measure the effectiveness of data products.
• Conduct post-launch evaluations, gathering feedback and performance data to drive continuous improvement.
• Monitor usage patterns, adoption rates, and business impact of data solutions.
• Identify areas for optimization and recommend enhancements to improve data products over time.

• 7 Data Governance & Compliance
• Ensure that data products adhere to data governance, security, and regulatory standards.
• Work closely with data stewards and compliance teams to enforce best practices in data management.
• Define data access policies, quality standards, and validation processes.

• 8 Innovation & Continuous Improvement
• Stay up to date with trends in data analytics, AI, machine learning, and cloud technologies.
• Research and recommend third-party solutions or integratio

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