Senior Engineering Manager

Senior Engineering Manager – Data & AI is responsible for leading high-performing engineering teams that deliver scalable data products, AI/ML capabilities, analytics foundations, and reliable platforms across Maersk. The role combines people leadership, stakeholder partnership, product delivery, data architecture, and operational excellence to translate business priorities into secure, resilient, production-grade technology solutions. It requires strong experience in data engineering, cloud platforms, AI-assisted development, engineering governance, and end-to-end delivery from prototype to production adoption.

JL5 Senior Engineering Manager – Data & AI team

WHO WE ARE

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.

The Position

As a Senior Engineering Manager in the Data & AI team, you will lead engineering teams responsible for delivering scalable data products, AI-enabled capabilities, analytical foundations, and reliable platforms that power critical business decision-making across Maersk.

You will be accountable for building and engaging a high-performing team, shaping pragmatic data architecture, partnering with product and business stakeholders, and ensuring successful delivery of data, analytics, and AI/ML solutions. The role requires a hands-on, forward-looking leader who can connect business problems to technical outcomes, guide teams from quick prototypes to production-grade products, and leverage modern AI coding agents to accelerate experimentation, solution design, and engineering delivery.

Key Responsibilities

Team Leadership, Engagement & Engineering Management

Build, lead, coach, and engage high-performing engineering teams across data engineering, AI/ML engineering, analytics enablement, and platform delivery

Create clarity on priorities, ownership, ways of working, delivery commitments, and engineering expectations across the team

Support resource and demand planning, capability building, knowledge sharing, and continuous development of team members

Stakeholder Management, Requirements & Business Partnership

Collaborate with product owners, business stakeholders, leadership, architecture, data science, and platform teams to understand business priorities and translate them into executable technology outcomes

Act as a trusted partner and voice of customer success by ensuring solutions address real business needs, adoption, usability, operational reliability, and measurable value

Drive clarity on requirements, trade-offs, timelines, risks, dependencies, and priorities across cross-functional stakeholders

Product Delivery, Prototyping & Innovation

Lead end-to-end delivery of data products, analytics capabilities, AI/ML solutions, dashboards, and platform capabilities from discovery through production adoption

Guide teams to quickly validate ideas through prototypes, proofs of concept, and iterative delivery before scaling validated solutions

Use modern AI coding agents and engineering automation to accelerate prototyping, solution exploration, developer productivity, and delivery effectiveness

Data Architecture, AI/ML Engineering & Platform Excellence

Shape scalable, governed, secure, and reusable data architecture across data engineering, analytics, visualization, AI/ML, and GenAI use cases

Provide technical leadership on data modelling, data pipelines, orchestration, cloud data platforms, integration patterns, and production-grade AI/ML engineering practices

Ensure solutions are horizontally scalable, resilient, observable, secure, and aligned with enterprise architecture and information security expectations

Cross-Functional Delivery & Architecture Governance

Partner across Product, Analytics, Data Science, AI, Platform, Architecture, Security, and business teams to deliver pragmatic end-to-end solutions

Translate business requirements, user feedback, and problem statements into delivery roadmaps, technical direction, architectural decisions, and implementation plans

Drive informed decision-making by balancing speed, quality, resilience, scalability, cost, security, and business value

Support integrations across cloud, enterprise applications, and data ecosystems

Operational Excellence

Champion engineering excellence, DevOps/DataOps practices, Site Reliability principles, observability, monitoring, incident management, and continuous improvement

Ensure team-owned products and platforms are reliable, scalable, secure, supportable, and production-ready

Drive automation, operational readiness, support models, and continuous learning across data, analytics, and AI/ML solutions

Our Ideal Candidate

Experienced engineering leader with proven ability to build, manage, coach, and engage high-performing teams

Strong stakeholder management skills with the ability to engage business, product, leadership, architecture, and platform stakeholders

Strong product delivery mindset with experience taking ideas from discovery and prototype through production adoption and continuous improvement

Hands-on technical leader with solid understanding of data engineering, SQL, data modelling, data pipelines, orchestration, cloud platforms, visualization, and AI/ML engineering concepts

Comfortable using AI coding agents and modern engineering tools to rapidly prototype solutions, test ideas, and accelerate delivery

Skilled communicator and collaborator with strong ownership, problem-solving ability, and passion for continuous learning and innovation

Required Skills/Experience

MS or BS in a Computer Science or Engineering discipline.

More than 10 years of technology experience, including significant experience leading engineering teams and delivering data, analytics, platform, or AI/ML products

Experience managing team priorities, delivery commitments, stakeholder expectations, resource planning, and capability development

Strong understanding of data architecture, SQL, data modelling, data pipelines, orchestration, cloud data platforms, visualization enablement, and AI/ML engineering practices

Experience with cloud-ready, scalable, resilient, secure, observable, and high-availability platforms and products

Hands-on familiarity with AI-assisted development, AI coding agents, or modern engineering automation for rapid prototyping and productivity improvement

Experience with DevOps, DataOps, Site Reliability principles, CI/CD, monitoring, observability, information security, troubleshooting, 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 accommodationrequests@maersk.com .

CORE SKILLS

• AI & Machine Learning: The field of artificial intelligence (AI) involves creating systems that can perform tasks that typically require human intelligence. Machine learning (ML) is a subset of AI that uses algorithms to learn from and make predictions based on data
• Proficiency Level: Advanced

Data Pr