As a
Data Engineer at A.P. Moller – Maersk
, you will design, build, and scale robust data solutions that power global logistics, supply chain visibility, and operational intelligence. You will play a key role in building cloud-native data platforms, enabling advanced analytics, and ensuring high-quality, reliable, and secure data pipelines across enterprise systems.
You will collaborate closely with product managers, data scientists, analysts, and cross-functional engineering teams to deliver scalable and resilient data products that drive business impact.
Key Responsibilities
Data Engineering & Architecture
- Design, develop, and maintain scalable batch and real-time data pipelines.
- Build and optimize data ingestion frameworks integrating multiple internal and external data sources.
- Architect and implement cloud-native data platforms using modern data stack technologies.
- Ensure data quality, lineage, observability, and governance best practices.
Platform & Performance
- Optimize data models and pipelines for performance, scalability, and cost efficiency.
- Implement CI/CD pipelines and infrastructure-as-code for data solutions.
- Improve system reliability through monitoring, logging, and automated alerting.
- Drive data platform standardization and reusable frameworks.
Collaboration & Stakeholder Engagement
- Partner with business stakeholders to translate requirements into technical data solutions.
- Work closely with data scientists and analytics teams to enable advanced reporting and ML use cases.
- Provide technical mentorship to junior and mid-level engineers.
- Contribute to design reviews and architectural discussions.
Governance, Security & Compliance
- Ensure adherence to enterprise data governance, security, and compliance policies.
- Implement role-based access control and secure data handling practices.
- Support audit readiness and regulatory requirements where applicable.
Required Qualifications
- Bachelor’s or Master’s degree in Computer Science, Engineering, or related field.
- 6–10 years of experience in data engineering or related software engineering roles.
- Strong proficiency in Python, SQL, and Spark.
- Hands-on experience with cloud platforms (Azure / AWS / GCP).
- Experience with data orchestration tools (Airflow, ADF, or similar).
- Expertise in building data warehouses/lakehouses (Snowflake, Databricks, BigQuery, etc.).
- Strong understanding of data modeling (star schema, dimensional modeling).
- Experience working with distributed systems and large-scale datasets.
Preferred Qualifications
- Experience in logistics, supply chain, or enterprise-scale environments.
- Exposure to streaming technologies (Kafka, Event Hubs).
- Knowledge of DevOps practices and Infrastructure-as-Code (Terraform, ARM, CloudFormation).
- Understanding of data governance tools and frameworks.
- Experience supporting AI/ML data pipelines.
Behavioral Competencies
- Strong problem-solving and analytical mindset.
- Ability to work in a fast-paced, global environment.
- Excellent communication and stakeholder management skills.
- Ownership mindset with a focus on delivering business value.
- Continuous learning and innovation-driven approach.
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 accommodationrequests@maersk.com.
