About this role
DHL Express - a company that connects people!
What makes DHL great? Our People! We know each employee’s individual contributions make us the #1 Express Delivery and Logistics Company in the world.
DHL Express is committed to maintaining an environment that empowers every team member to make the greatest possible impact on our business. Our corporate culture is about personal commitment – to our business, to each other and to our global communities. DHL is dedicated to being a great place to work. Start YOUR career with DHL today…
Role Purpose
The Manager, Reporting & Business Analytics owns the delivery, accuracy, and relevance of reporting, metrics, and customer behaviour insight across DHL's DCS digital product portfolio. The role is the subject-matter expert for the metrics the organization measures and the data sources behind them, and coordinates with IT counterparts who build and maintain dashboards and reporting assets to ensure insight products are accurate, timely, and fit for purpose.
The role continuously monitors the health and customer experience of DCS applications using established instrumentation (including Adobe Analytics, Medallia Decibel, and Medallia Voice of Customer), logs findings in the friction log, and works with Product Owners to resolve issues that affect the customer experience. The role also partners with Business Intelligence to bring product and interaction data into the Data Lake and stitches that data together to build an end-to-end view of customer behaviour across the DCS product portfolio.
This is an individual-contributor, subject-matter-expert role with no direct reports. The role works in a matrix capacity with colleagues in the IT organization who deliver the technical build, and partners closely with Product Owners, Business Intelligence, and the wider Data Insights & Analytics team.
How will you contribute to the success of DHL?
Reporting & Dashboard Delivery
- Develop, maintain, and refresh reporting dashboards and analytics assets, providing requirements, priorities, and acceptance criteria.
- Manage the reporting life cycle end to end, from requirements and metric definitions through development, quality assurance, release, adoption, and continuous improvement.
- Ensure dashboards and reports remain accurate, timely, reliable, and aligned to stakeholder needs.
Metrics & Data Source Subject-Matter Expertise
- Build and configure Adobe Analytics reports, segments, calculated metrics, and workspaces to extract the data needed for KPI tracking and ad hoc analysis.
- Define, document, and maintain consistent KPI definitions, calculation logic, and data lineage, aligned to organizational standards.
- Partner with Product Owners, Business Intelligence, and IT to ensure measurement is complete, trusted, and decision ready.
Health & Customer Friction Monitoring Application
- Monitor the health and customer experience of DCS applications using established instrumentation, including Adobe Analytics reports, Medallia Decibel customer replays, and Medallia Voice of Customer feedback.
Data Lake Integration & End-to-End Customer Behaviour
- Work with Business Intelligence counterparts to define requirements for ingesting relevant products and interaction data into the Data Lake.
- Specify data mappings, identifiers, and quality/validation rules needed for trusted cross-product analysis.
- Stitch user interactions and digital footprints together to build an end-to-end view of customer behavior across the DCS product portfolio (e.g. discovery, adoption, engagement, friction, conversion).
Reporting, Analysis & Stakeholder Communication
- Compile, analyze, and distribute reporting and insights to team members and key stakeholders on regular cadence.
- Identify trends, anomalies, and root causes in performance data, and recommend corrections or enhancements.
- Escalate material findings and negative trends to relevant stakeholders in a timely manner.
AI-Enabled Analytics & Productivity
- Apply AI and automation tools (e.g. AI-assisted analytics platforms, LLM-based query and summarization tools, anomaly-detection features in Adobe Analytics/Medallia) to speed up reporting, friction-log analysis, and insight generation.
- Use AI responsibly: validate AI-generated outputs against source data, apply human judgement before sharing insights with stakeholders, and follow enterprise data governance and privacy requirements when using AI tools on customer data.
- Stay current on AI and analytics tooling trends relevant to digital product analytics and bring forward recommendations to improve team productivity and insight quality.
Do you have what it takes?
- University degree in Business, Analytics, Data Science, Computer Science, Marketing, or a related field, or equivalent professional experience.
- Professional certification in a relevant analytics, data, or project management discipline is an advantage.
- Minimum 6 years of experience in reporting, digital/product analytics, business intelligence, or a related field (or equivalent combination of education and experience).
- Practical experience with Adobe Analytics and digital customer journey analysis.
- Experience using session-replay and Voice of Customer platforms (e.g. Medallia, Decibel, FullStory, Amplitude) is preferred.
- Experience defining and governing KPIs, metrics, and data sources across multiple products or teams.
- Experience coordinating delivery with IT, Business Intelligence, or data engineering teams, including through matrix/dotted line working relationships.
- Hands-on proficiency building dashboards and reports in Power BI, Tableau, or an equivalent BI tool, including data modelling, calculated fields/measures, and visual design best practices.
- Hands-on proficiency building and maintaining reports, segments, and calculated metrics in Adobe Analytics (or equivalent web/product analytics platform), and using that output to populate and validate KPI dashboards.
- Working knowledge of dashboards/BI tools, Data Lakes, data pipelines, event-level data, and data lineage concepts, and how they support cross-product customer journey analysis.
- Practical experience using AI-assisted analytics, automation, or generative AI tools (e.g. Copilot, ChatGPT, or similar) to accelerate reporting, data analysis, or insight generation.
- Comfortable evaluating new AI-enabled analytics capabilities and applying them pragmatically to real reporting and analysis workflows, with appropriate judgement on when human validation is required.
- Sound understanding of data governance, privacy, and security principles relevant to customer-interaction data.
- Ability to translate complex data into clear, actionable recommendations for business and product stakeholders.
- Strong written and verbal English, with the ability to work effectively across cultures, regions, and organizational boundaries.
DHL is an equal opportunity employer. We evaluate qualified applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, or any other protected characteristic.
Recruitment Fraud Alert: DHL Express will never request payment or personal/financial information from applicants or employees at any stage of the recruitment process. Any such request should be treated as fraudulent. All email correspondence will be sent from the official DHL domain e.g. [email protected]. Protect yourself by verifying job offers and communications.
Your safety is important to us.