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Maersk

Global container shipping and end-to-end logistics

Senior Data Engineer

Data EngineeringConfirmed live in the last 24 hours
Full-timeNo salary listed

About the Job

Requirements

  • Hands-on experience with Azure Databricks (SQL/PySpark), ADLS, and Azure Data Factory.
  • Hands-on experience with Azure Analysis Services and Power BI/Fabric modelling, including DAX.
  • Strong SQL and Python skills.
  • First hands-on experience using AI, such as coding assistants or agents, to support work, and curiosity to develop further.
  • Ability to explain technical trade-offs clearly to non-technical stakeholders and push back constructively on scope.
  • Ability to turn ambiguous requests into clear requirements and scalable solutions.
  • Ability to work in a globally distributed team with clear written communication and handovers.
  • Ability to take end-to-end ownership, mentor others, and share knowledge.
  • Comfort 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.
  • At least 5 years of experience in data engineering and/or BI engineering.

Responsibilities

  • Design, build, and run scalable data pipelines in Azure Databricks (SQL/PySpark) on ADLS, orchestrated with Azure Data Factory and 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 monitoring and refresh of scheduled pipelines and models, including root-cause analysis when failures occur.
  • Maintain runbooks, documentation, and lineage so the landscape can be supported by more than one person.
  • Apply Git-based version control, code review, and development-to-production 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 data AI-ready.
  • Build reusable components and automation that reduce manual effort and scale the reporting landscape.
  • Introduce and champion 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.

Desired Qualifications

  • Experience with Dremio or similar query layers.
  • Experience with MDX.
  • Experience migrating from Azure Analysis Services to Power BI semantic models on Databricks.
  • Knowledge of commercial or finance reporting.

About the Company

Maersk

Global container shipping and end-to-end logistics

Maersk is an integrated logistics provider that connects and simplifies customers’ supply chains through global shipping and end-to-end logistics services. Its offerings span ocean freight, inland transportation, warehousing, and supply chain management, all coordinated with digital tools that give customers visibility and control over shipments. Unlike traditional shipping lines, Maersk positions itself as a comprehensive logistics partner that integrates multiple modes of transport and services to create seamless, transparent supply chains. The company pursues a global reach—operating in 130 countries with more than 100,000 employees—to serve businesses of all sizes. Its goal is to make global trade smoother by delivering end-to-end logistics solutions that unify what moves by sea, land, and in between.

Company size
10,001+
Company stage
IPO
Headquarters
Copenhagen, Denmark
Founded
1904

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