Senior Data Engineer

Do you want to build the data foundation behind how a global logistics leader steers its commercial businessAs a Senior Data Engineer in our Commercial Data Products Reporting team, you will own the pipelines, semantic models and reporting data behind a governed portfolio of global standard reports. This is the one set of numbers used by sales leadership, finance business partners and area teams worldwide.

You will join a small, integrated team of Product Owners, Reporting Analysts and engineers across Denmark and India. Engineering and reporting are built as one product, not handed over between silos. You will be the technical anchor for the data layer and cover the whole chain:

• Ingestion and transformation in Azure Databricks and ADLS.
• Orchestration in Azure Data Factory.
• Semantic models in Azure Analysis Services (AAS) and Power BI / Fabric, which our dashboards and reports are built on.

We are evolving our semantic layer and using AI assistants and agents in our engineering work. You will help shape both.

• Design, build and run scalable data pipelines in Azure Databricks (SQL/PySpark) on ADLS, orchestrated with Azure Data Factory, integrating multiple ERP and operational source systems.
• Design, maintain and optimize Azure Analysis Services models and Power BI / Fabric semantic models, moving business logic upstream into the data platform where it improves performance and maintainability.
• Work with Product Owners and Reporting Analysts to turn requirements into governed data products, dashboards and reports.

• Own the monitoring and refresh of scheduled pipelines and models, including root-cause analysis when something fails.
• Maintain runbooks, documentation and lineage so the landscape can be supported by more than one person.
• Apply Git-based version control, code review and dev-to-prod promotion, and uphold data quality and governance standards.

• Use AI assistants and agents in everyday engineering work, for example for code, testing and documentation, and help make our data AI-ready.
• Build reusable components and automation that reduce manual effort and scale the reporting landscape.
• Introduce and champion new technologies and practices that improve efficiency, scalability and cost.

• Coach Reporting Analysts and new colleagues on engineering good practice.
• Share knowledge openly, so that no capability depends on a single person.

You don\'t need to tick every box. If you match most of the core requirements, we would like to hear from you.

• Backend engineering: hands-on experience with Azure Databricks (SQL/PySpark), ADLS and Azure Data Factory.
• Semantic layer: hands-on experience with Azure Analysis Services and Power BI / Fabric modelling (including DAX).
• Core languages: strong SQL and Python.
• AI: first hands-on experience using AI, such as coding assistants or agents, to support your work, and the curiosity to go further.
• Nice to have: Dremio or similar query layers, MDX, experience migrating from AAS to Power BI semantic models on Databricks, and knowledge of commercial or finance reporting.

• You explain technical trade-offs clearly to non-technical stakeholders and push back constructively on scope.
• You turn ambiguous requests into clear requirements and scalable solutions.
• You work well in a globally distributed team, with clear written communication and handovers.
• You take ownership end to end, you mentor others, and you share knowledge generously.
• You are comfortable with Agile ways of working and tools such as Jira.

• Bachelor\'s or Master\'s degree in Data Engineering, Computer Science, Information Systems or a related field, or equivalent practical experience.
• 5+ years of experience in data engineering and/or BI engineering.

• End-to-end ownership of a data stack, with a direct line to the product owners and business users who rely on it.
• Visible impact: data used by Commercial leadership and area teams around the world.
• Hands-on adoption of AI and agents in your engineering work.
• A learning-focused environment with a clear career framework, defined skills and proficiency levels by job level.
• The chance to work in an integrated team where data engineering and reporting are built as one product.

Note: The position can be based in either Pune or Bangalore.