Data Engineer

Maersk’s bold leap into the future of data and AI. It’s not just a platform-it’s a transformation of how the world’s largest integrated logistics company turns its operational data into strategic intelligence. Think: real-time insights on vessel ETA and carbon emissions, metadata-driven supply chain automation, and retrieval-augmented copilots that advise planners and operators. Our data engineers don’t just build pipelines-they shape the very foundation that powers AI-native logistics. You’ll help modernize and operationalize Maersk’s global data estate. You’ll craft reusable, observable, and intelligent pipelines that enable ML, GenAI, and domain-specific data products across a multi-cloud environment. Your code won’t just move data-it’ll move trade.
What You'll Be Doing

• Ingest the world: Design and maintain ingestion frameworks for high-volume, structured and unstructured data-from operational systems, APIs, file drops, and events. Support streaming and batch use cases across latency windows.
• Transform at scale: Develop transformation logic using SQL, Python, Spark, and modern declarative tools like dbt or sqlmesh. You’ll handle deduplication, windowing, watermarking, late-arriving data, and more.
• Curate for trust: Collaborate with domain teams to annotate datasets with metadata, ownership, PII classification, and usage lineage. Enforce naming standards, partitioning schemes, and schema evolution policies.
• Optimize for the lakehouse: Work within a modern lakehouse architecture-leveraging Delta Lake, S3, Glue, and EMR-to ensure scalable performance and queryability across real-time and historical views.
• Build for observability: Instrument your pipelines with quality checks, cost visibility, and lineage hooks. Integrate with OpenMetadata, Prometheus, or OpenLineage to ensure platform reliability and traceability.
• Enable production-readiness: Support deployment workflows via GitHub Actions, Terraform, and IaC patterns. Your code will be versioned, testable, and safe for multi-tenant deployments.
• Think platform-first: Everything you build should be reusable. You’ll help codify data engineering standards, create scaffolding for onboarding new datasets, and drive automation over repetition.

What We’re Looking For-

Must-Haves

• Python(PySpark) & SQL — Non-negotiable. Strong working proficiency in both.
• AWS — Solid understanding of AWS services beyond just data engineering (storage, compute, networking, IAM, etc.). Preference for candidates already working within the AWS ecosystem.
• Data Fundamentals & Data Pipeline Optimization — Working knowledge of optimizing pipelines for cost efficiency and resource utilization.
• Interest in working in Platform Engineering

Good to Have

• Platform Engineering Mindset — Must have a genuine interest in platform/infrastructure work, not just pipeline development. Cultural fit on this is important — we don't want drop-offs post-interview.
• Containerization & Orchestration — Conceptual understanding or hands-on experience with Docker and Kubernetes.
• Cloud Migration / Multi-cloud — Experience with cloud migrations or working across multi-cloud environments.
• AI/ML — Any exposure to AI/ML concepts or tooling is a bonus, not a requirement.
• Infrastructure as Code (IaC) — Familiarity with IaC tooling (Terraform, CDK, etc.).
• Observability — Familiarity with tools like Grafana and Prometheus for monitoring and alerting.

What Makes This Role Special

• Impact at global scale: Your work will influence container journeys, terminal operations, vessel routing, and sustainability metrics across 130+ countries and $4T+ in global trade.
• Platform-level thinking: You’re not just solving one use case-you’re building primitives for others to reuse. This is your chance to shape a high-leverage internal data platform.
• Freedom to experiment: We don’t believe in checkbox engineering. You’ll have space to challenge the status quo, propose better tooling, and refine the foundations of our platform stack.
• Career-defining scope: Greenfield. Executive visibility. Cross-domain exposure. This is not a maintenance role-it’s about creating the next chapter in Maersk’s data journey.

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.

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