Data Engineer

Fleet Management Limited

Our 30-year journey rides on the passion of over 27,000 seafarers and 1,000 onshore professionals. Today, we are one of the largest independent third-party ship management companies managing over 650+ diverse types of vessels.

Headquartered in Hong Kong SAR, China, we operate on a global scale having 27 offices in 12 countries. Our client base spans over 100 world-class ship owners, including Fortune 500 companies from China, Greece, India, Japan, Korea, Netherlands, Norway, Turkey and the USA, among others.

In a shore career at Fleet, you will be working with a team of a highly passionate, self-driven and committed group of people. We aim to be a place where you can achieve your full potential, regardless of your background.

We are looking for individuals who are ambitious about making a strong contribution to Fleet's short and long-term sustainable growth – whether you are dealing directly with clients or working in a role supporting the business, such as technology, legal or communications.

As a Data Engineer, your typical day will cover the following areas:

1. Build & Optimise Data Systems

(Focus: Core engineering work with a balance of pipelines and infrastructure)

• Create & maintain data highways: Develop and manage cloud-based data lakes, warehouses, and ETL/ELT pipelines that ingest, process, and deliver data from 630+ ships and external sources

• Keep systems shipshape: Monitor cloud infrastructure performance, resolve bottlenecks, and ensure scalability/reliability for 24/7 maritime operations—no room for “set and forget.”

• Secure the cargo: Implement data quality checks, encryption, and compliance standards (GDPR, SOC2) to protect sensitive maritime telemetry and operational data

• Automate the mundane: Use tools like Airflow to streamline workflows and reduce manual intervention in pipeline maintenance

2. Support Analytics & Troubleshoot Issues

(Focus: Enabling insights while keeping systems running smoothly)

• Fuel AI/ML engines: Partner with Data Scientists to prep datasets for predictive models (e.g., fuel efficiency, preventative maintenance, etc.) and troubleshoot pipeline issues impacting their work

• Solve data mysteries: Diagnose root causes of pipeline failures, data discrepancies, or MLOps hiccups—then implement fixes that prevent repeat headaches

• Map the data terrain: Document source-to-target mappings, conduct data profiling, and clarify dependencies so analysts can self-serve without guesswork

• Stay curious: Experiment with new tools and techniques to improve data quality, system performance and pipeline resilience

3. Collaborate & Learn

(Focus: Teamwork and growth in a fast-paced environment)

• Be the glue: Work closely with onshore and offshore developers, IT Operations, and stakeholders across Fleet to deliver solutions that balance technical rigor with real-world usability

• Communicate clearly: Break down complex data concepts for non-technical audiences (think ship captains, not just engineers) and ask questions to avoid ambiguity

• Learn by doing: Shadow senior engineers, participate in code reviews, and absorb best practices to level up your craft—no prior maritime experience required, but curiosity is a must.

Essential :

• 3+ years’ experience in a Data Engineering role using SQL, PySpark and AirFlow

• Strong understanding in Data Lake and Data Warehouse design best practices and principles

• Practical hands-on experience in cloud-based data services for ETL/ELT covering AWS EC2, S3 Storage and EMR

• Ability to manage and enhance infrastructure related to environments covering Spark, Hive, Presto

• Experience with databases such as Postgres, MySQL, Oracle

• Strong work ethic and ability to work independently on agreed goals

• Clear communication skills in English – both in speaking and writing

Desirable :

• Deployment experience and management of MLOps framework, such as AWS SageMaker AI, ECR

• Experience in other cloud platform and hybrid cloud infrastructure, e.g. GCP, Azure

• Experience in the maritime industry