**About DHL:** ------------------ We are the world’s leading logistics company, creating a competitive advantage for our customers by providing logistics solutions based on our warehousing, transportation, and standardized integrated services worldwide. Our people are our greatest asset. We are certified as a Great Place to Work company. At DHL, you’ll find a culture that embraces diversity and collaboration; empowers your strengths; and builds trust through our values of respect and results. A world powered by logistics. A company powered by our people.**Job Objective** ----------------------- The Analytics Engineer will be responsible for transforming raw data originating from multiple systems and areas (transportation, warehousing, IT, etc.) into structured and reliable models aligned with global standards—or developing new models where none exist. This role bridges business understanding with solid data engineering practices, ensuring quality, governance, and scalability in delivering analytical products for Mexico and LATAM. The role will primarily use Databricks, SQL, PySpark, Python, and Azure, playing a key part in standardizing and reusing models to drive efficiency and value for the organization.**Key Responsibilities** --------------------------- \- Transform and organize large volumes of data into structured models aligned with the global architecture. \- Develop scalable transformation processes using Databricks (SQL/PySpark) and Azure Data Services. \- Design efficient pipelines, optimizing cost and performance while meeting SLAs and compute windows. \- Ensure models comply with governance, security, documentation, and certification standards. \- Assess data sources, identify quality issues, and define transformation logic to ensure reliability. \- Propose reusable patterns and templates to accelerate future analytics and digitalization initiatives. \- Create technical and business documentation (lineage, rules, constraints, assumptions). \- Implement data quality validations and automated testing. \- Collaborate with business and operations teams to reflect real-world processes in models. \- Communicate technical decisions and complex concepts to non-technical stakeholders. \- Participate in the Analytics & Data community, sharing knowledge and best practices. Work with regional and global teams to co-develop technology solutions.**Who We’re Looking For** -------------------- Technical Profile: • Minimum 3+ years in analytics engineering, BI, or data modeling, ideally in logistics or supply chain environments. • Proficiency in SQL, Databricks, PySpark, Delta Lake, and cloud environments (preferably Azure). • Experience designing and maintaining data models and transformation pipelines. • Knowledge of data product practices: documentation, certification, testing, governance. • Familiarity with transportation, warehousing, or logistics data is desirable. • Knowledge of visualization tools (Power BI, Tableau) is a plus. Functional Profile: • Ability to translate business rules into models and transformation logic. • Collaboration and influence skills without formal authority across technical and business teams. • Clear communication and storytelling skills to explain modeling structures and decisions. Education and Qualifications: • Bachelor’s degree in Data Science, Engineering, Computer Science, Applied Mathematics, or related fields. • Certifications in Databricks, Azure, or data modeling are a plus. • Intermediate-to-advanced English. How We’ll Measure Your Success: • Measurable improvement in data quality and reliability. \- Efficiency enabled by standardized and reusable models. \- Frequency of data products replicated across other projects or regions. \- On-time delivery of modeling components and data products. \- Compliance with documentation, governance, and certification standards. \- Stakeholder satisfaction with the usability and reliability of data products.