Business Analyst - Data Products

Descrição do trabalho

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