Job Description

Maersk, the world’s largest integrated logistics company, is transforming how goods move across continents - and at the heart of that shift is data infrastructure . We are building MIDAS , a modern, federated, metadata-driven data platform engineered for composability, governance, and AI-readiness.

We are hiring a Senior Engineering Manager to lead platform engineering efforts for MIDAS - designing and scaling a multi-tenant, real-time, contract-first data platform that spans hundreds of internal systems and supports critical customer and operational use cases.

This is not just a leadership role. It’s a once-in-a-decade opportunity to build the foundational data and AI architecture for an entire industry .

What You’ll Lead and Architect

  • Contract-Driven Data Pipelines powered by Apache Iceberg, Kafka, and Airflow with CI/CD for ingestion and transformation logic

  • Policy-as-Code Frameworks using OPA/Rego for automated enforcement of ABAC, retention, masking, and lineage propagation

  • Multi-Modal Metadata Plane integrating OpenMetadata or DataHub for discoverability, glossary, certification, and observability

  • Data Mesh Enablement for 300+ domain teams through onboarding blueprints, QuickStart DAGs, SLOs, and governance scaffolds

  • AI/ML Infrastructure Foundation – feature store integration, model monitoring hooks, ML lineage tracking, and model artifact versioning

  • Scalable Runtime Architecture supporting containerized deployments, tenant isolation, RBAC, and declarative ownership models

    • You will also define the engineering strategy for GenAI enablement , with LLM-based copilots and inference patterns backed by real-time streaming and vector-indexed feature stores.

    Scale & Complexity You’ll Tackle

  • 20M+ containers , 700+ vessels, 100K+ customers across 130+ countries

  • $4 trillion of global GDP flows through Maersk's digital backbone

  • 300+ business applications with heterogeneous schemas and integration models

  • Cross-functional federation involving Ops, TradeLens, GDA, Corp, TbM, and more

  • Mission-critical workloads: ETA predictions, vessel tracking, customer order visibility, emissions analytics, and autonomous logistics intelligence

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