Senior Data Engineer

A.P. Moller - Maersk; København; On-site; DKK 900,000 - 1,200,000; Full time

Job summary

A.P. Moller - Maersk is seeking a Senior Data Engineer to design, build, and operate scalable data products and pipelines that power business insights and AI-enabled decision-making.

You will collaborate with Analytics, Platform, and AI teams to enable fast, reliable data-driven outcomes. In this role, you will apply SQL, Python, and PySpark to transform complex data into trusted datasets, support governance, and deliver visualization-ready data for stakeholders across the enterprise.

Qualifications

• Advanced SQL skills and data modeling for analytics
• Hands-on Python/PySpark for large-scale data processing
• Experience building scalable batch/streaming data pipelines

Responsibilities

• Design, build, and operate scalable data pipelines and data products
• Collaborate with analytics, product, and platform teams to enable self-service data
• Ensure data quality, governance, and lineage across data platforms
• Support AI/ML enablement with robust data foundations

Skills

SQL

Python

PySpark

Data pipelines

Data modeling

Cloud platforms

Education

BS in Computer Science or related field

Tools

Airflow

Databricks

Job description

A.P. Moller - Maersk is an integrated container logistics company and member of the A.P. Moller Group. Connecting and simplifying trade to help our customers grow and thrive. With a dedicated team of over 80,000, operating in 130 countries; we go all the way to enable global trade for a growing world. We leverage cutting-edge technology to optimize operations, enhance customer experience, and drive business growth. We are seeking a Senior Data Engineer to join our team and play a pivotal role.

About The Role

At Maersk, we are redefining global logistics through data, platform engineering, and AI-driven innovation. As part of this journey, we are building scalable platforms and intelligent systems that enable faster decision-making, operational efficiency, and seamless integration across the enterprise. As a Senior Data Engineer, Data & AI, you will design, build, and operate scalable data products, pipelines, and analytical foundations that power business insights, critical business capabilities, and AI-enabled decision-making.

Key Responsibilities

• Data Engineering, Pipelines & Orchestration
• Design, build, and optimize scalable batch and streaming data pipelines using modern data engineering patterns
• Develop robust orchestration workflows for dependable data ingestion, transformation, quality checks, and downstream consumption
• Apply strong SQL, Python, and PySpark skills to transform complex data into reliable, reusable, and performant data products
• SQL, Data Modelling & Analytics Enablement
• Create well-modelled, trusted datasets that support reporting, visualization, advanced analytics, and AI/ML use cases
• Enable self-service data access and governed consumption by building clear data contracts, documentation, and quality controls
• Contribute to integrated data foundations that provide consistent, reusable data across business domains and platforms
• Visualization, BI & Data Product Delivery
• Partner with analytics and product teams to deliver high-quality datasets, dashboards, and visualization-ready semantic layers
• Translate business requirements into scalable data models and consumption patterns for operational and executive insights
• Support adoption of data products by ensuring performance, usability, reliability, and clear lineage from source to insight
• AI/ML Engineering Enablement
• Build data pipelines and feature-ready datasets that support machine learning, AI, and GenAI use cases
• Collaborate with data scientists and AI engineers to productionize models, automate data refreshes, and improve repeatability
• Apply engineering practices for monitoring, testing, versioning, and operationalizing data and ML workflows
• Cross-Functional Delivery & Architecture
• Work with Product, Analytics, Platform, Data Science, AI teams, and business stakeholders to clarify requirements and deliver pragmatic end-to-end data solutions
• Translate business requirements, user feedback, and problem statements into data models, working prototypes, technical designs, and implementation plans
• Contribute to data architecture discussions and ensure alignment with enterprise standards, security, and governance expectations
• Support integrations across cloud and enterprise data ecosystems
• Operational Excellence
• Ensure data solutions are reliable, scalable, performant, secure, and production-ready
• Monitor, troubleshoot, and continuously improve pipeline performance, data quality, and platform stability
• Drive automation, observability, and supportability across data, analytics, and AI/ML solutions

Our Ideal Candidate

• Strong data engineering experience with hands-on delivery of scalable data pipelines, data products, and analytics foundations
• Advanced SQL skills with the ability to design performant queries, data models, and transformation logic
• Hands-on knowledge of Python and PySpark for large-scale data processing and automation
• Curious, hands-on problem solver who can engage with business stakeholders to understand the real requirement and deliver practical outcomes
• Comfortable moving between rapid prototyping and production-grade data engineering based on business need
• Experience enabling visualization, BI, AI/ML, or advanced analytics through trusted and well-governed data foundations
• Familiarity with cloud data platforms, orchestration tools, and distributed data processing patterns
• Strong ownership mindset and ability to work effectively across teams

Required Skills/Experience

• MS or BS in Computer Science or a science/engineering discipline
• More than 6 years of experience in data engineering, analytics engineering, or data platform delivery
• Strong proficiency in SQL, Python, and PySpark is required
• Experience designing and operating ETL/ELT pipelines, orchestration workflows, data quality checks, and production data products
• Experience with cloud data platforms, distributed processing, data modelling, and analytics/BI consumption patterns
• Exposure to AI/ML engineering practices, feature pipelines, model productionization, LLM-based applications, or agentic AI patterns will be an added advantage
• Experience with DevOps and DataOps practices, including CI/CD, monitoring, observability, and incident support

Maersk is committed to a diverse and inclusive workplace, and we embrace different styles of thinking. Maersk is an equal opportunities employer and welcomes applicants without regard to race, colour, gender, sex, age, religion, creed, national origin, ancestry, citizenship, marital status, sexual orientation, physical or mental disability, medical condition, pregnancy or parental leave, veteran status, gender identity, genetic information, or any other characteristic protected by applicable law. We will consider qualified applicants with criminal histories in a manner consistent with all legal requirements. We are happy to support your need for any adjustments during the application and hiring process. If you need special assistance or an accommodation to use our website, apply for a position, or to perform a job, please contact us by emailing [e-mail].