Senior Data Engineer

Job highlights

• • 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
• Coach Reporting Analysts and new colleagues on engineering good practice
• • 5+ years of experience in data engineering and / or BI engineering

About us Maersk is a global leader in integrated logistics and has been an industry pioneer for over a century. Through innovation and transformation, we are redefining the boundaries of possibility, continuously setting new standards for efficiency, sustainability, and excellence. Join us as we harness cutting-edge technologies and unlock opportunities on a global scale. Together, lets sail towards a brighter, more sustainable future with Maersk. To learn more about everything that Maersk does, visit us at www. maersk. com.

Do you want to build the data foundation behind how a global logistics leader steers its commercial business As 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.

About the Role

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.

Key Responsibilities
Build and own the data layer

• 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.

Keep it reliable

• 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.

Make it smarter

• 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.

Grow the team

• Coach Reporting Analysts and new colleagues on engineering good practice.

• Share knowledge openly, so that no capability depends on a single person.

What We re Looking For

You don t need to tick every box. If you match most of the core requirements, we would like to hear from you.

Technical skills

• 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.

How you work

• 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.

Qualifications

• 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.

What We Offer

• 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.

Maersk is committed to a diverse and inclusive workplace, and we embrace different styles of thinking.

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Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.