Job Description

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

Strong foundation in data engineering:

You know your way around

distributed systems

,

columnar storage formats (Parquet, Avro)

,

data lake performance tuning

, and

schema evolution

.

Hands-on cloud experience:

You've worked with

AWS-native services

like

Glue

,

EMR

,

Athena

,

Lambda

, and object storage (S3). Bonus if you've used

Databricks

,

Snowflake

, or

Trino

.

Modern engineering practices:

Familiarity with

GitOps

,

containerized workflows (Docker, K8s)

, and

CI/CD pipelines

for data workflows. Experience with

Terraform

and IaC is highly valued.

Programming proficiency:

Fluency in

Python

and

SQL

is a must. Bonus if you've worked with

Scala

,

Jinja-templated SQL

, or DSL-based modeling frameworks like dbt/sqlmesh.

Curiosity and systems thinking:

You understand the tradeoffs between batch vs streaming, structured vs unstructured, cost vs latency-and you ask why before you build.

Collaboration skills:

You'll work closely with ML engineers, platform architects, security teams, and domain data owners. Ability to communicate clearly and write clean, documented code is key.

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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