Data Engineer

Fleet Management Limited; Hong Kong; On-site; HKD 900,000 - 1,300,000; Full time

Job summary

Fleet Management Limited is seeking a Data Engineer to design and run scalable data pipelines powering real-time analytics for a global fleet. You will transform raw telemetry into actionable insights, support AI/ML models, and feed NOVA dashboards for internal and client use.

The role emphasizes cloud-based data platforms, data quality, and collaboration with onshore/offshore teams, with a focus on reliability in a maritime data environment. English communication is essential.

Qualifications

• 3+ years’ experience in a Data Engineering role using SQL, PySpark and Airflow.
• Strong understanding of 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 Spark and Trino environments and their supporting infrastructure.
• Experience with databases such as PostgreSQL, MySQL or Oracle.
• Strong work ethic and ability to work independently on agreed goals.
• Clear communication skills in English – both in speaking and writing.

Responsibilities

• Build & Optimise Data Systems: Develop and manage cloud-based data lakes, warehouses, ETL/ELT pipelines, and APIs that ingest, process, and deliver data from 600+ ships and external sources.
• Monitor cloud infrastructure performance, resolve bottlenecks, and ensure scalability and reliability for 24/7 maritime operations—no room for “set and forget”
• Implement data quality checks, encryption, and compliance standards to protect sensitive maritime telemetry and operational data
• Use tools like Airflow to streamline workflows and reduce manual intervention in pipeline maintenance

Skills

SQL

PySpark

Airflow

Data Lake design

Data Warehouse design

Cloud-based ETL/ELT

AWS EC2

S3 Storage

EMR

Spark

Trino

PostgreSQL

MySQL

Oracle

English communication

Tools

Airflow

AWS SageMaker

LangGraph

RAG

GCP

Azure

Job description

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.

Job Position Summary

At Fleet, we’re not just navigating the high seas—we’re charting the data currents that power the future of maritime intelligence.

As a Data Engineer, you’ll manage the invisible backbone of our analytics, building scalable data pipelines that fuel real-time insights for 600+ ships worldwide. Your work will turn raw data points into actionable intelligence, propelling machine learning models and AI-driven decisions that redefine how global fleets operate.

This isn’t just ETL; it’s mission-critical infrastructure. You’ll engineer systems that feed our NOVA analytics dashboards for both office colleagues and clients—ensuring our PARIS platform stays leagues ahead in a data-driven industry. If you’re someone who thrives on taming chaotic data streams into crystal-clear insights, let’s build the lighthouse that guides maritime innovation.

Key Roles and Responsibilities

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

Build & Optimise Data Systems:

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

• Develop and manage cloud-based data lakes, warehouses, ETL/ELT pipelines, and APIs that ingest, process, and deliver data from 600+ ships and external sources
• Monitor cloud infrastructure performance, resolve bottlenecks, and ensure scalability and reliability for 24/7 maritime operations—no room for “set and forget”
• Implement data quality checks, encryption, and compliance standards to protect sensitive maritime telemetry and operational data
• Use tools like Airflow to streamline workflows and reduce manual intervention in pipeline maintenance

Support Analytics & Troubleshoot Issues:

(Focus: Enabling insights while keeping systems running smoothly)

• Partner with Data Scientists to prepare datasets for predictive models (e.g., fuel efficiency and preventative maintenance) and troubleshoot pipeline issues impacting their work
• Diagnose root causes of pipeline failures, data discrepancies or MLOps hiccups—then implement fixes to prevent repeats
• Document source-to-target mappings, conduct data profiling, and clarify dependencies so analysts can self-serve without guesswork
• Experiment with new tools and techniques [VK1.1]to improve data quality, system performance and pipeline resilience

Collaborate & Learn:

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

• Work closely with onshore and offshore developers, IT Operations, and stakeholders across Fleet to deliver solutions that balance technical rigour with real-world usability
• Break down complex data concepts for non-technical audiences (think ship captains, not just engineers) and ask questions to avoid ambiguity
• Participate in code reviews and absorb best practices to level up your craft—no prior maritime experience required, but curiosity is a must

Relationship

INTERNAL:

• Development Teams (based in HK & India); Ops & Support (based in HK & India)

EXTERNAL:

• Third-party vendors for interfacing Data Sources
• Third-party Development Teams

Job Experience, Functional Knowledge and Qualifications

ESSENTIAL:

• 3+ years’ experience in a Data Engineering role using SQL, PySpark and Airflow
• Strong understanding of 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 Spark and Trino environments and their supporting infrastructure
• Experience with databases such as PostgreSQL, MySQL or Oracle
• Strong work ethic and ability to work independently on agreed goals
• Clear communication skills in English – both in speaking and writing

DESIRABLE:

• Experience deploying and managing MLOps frameworks, such as AWS SageMaker
• Experience working with AI frameworks and architectures, such as LangGraph and retrieval-augmented generation (RAG) systems
• Experience with other cloud platforms and hybrid cloud infrastructure, such as GCP and Azure
• Experience in the maritime industry
• Analysis & Problem Solving: Uses critical thinking to address problems. Able to perform root cause analysis on complex problems to identify underlying trends and put forward well‑thought‑out solutions to address the causes.
• Listening & Communication: Focuses on the individual they are communicating with. Writes and expresses thoughts clearly adjusting as necessary to the audience. Asks questions to clarify.
• Collaboration, Inclusion & Teamwork: A good team player that is personable, friendly, polite and takes the time to know people. Collaborates with onshore and offshore colleagues well.
• Customer Focus: Understands the needs of the customer clarifying requirements and expectations. Adapts as necessary to changing requirements and is responsive, helpful with all requests. Sets high quality for service delivery.
• Planning & Organising: Uses the supplied tools for structured project planning for optimal time use. Balances competing priorities. Promptly Updates people when plans change and keeps them apprised of progress. Adjusts own plans based on FML strategies and plans.
• Initiative: Challenges existing ways of doing things. Looking for continuous improvement without being asked. Identifies ways to improve efficiency and effectiveness in own work and others in the team.
• Accountability: Responsible for delivery own work without unnecessary supervision. Always demonstrates integrity and ethical behavior being a role model for others. Invites constructive feedback adjusting actions accordingly. Thinks through mistakes made and finds ways to prevent reoccurrence.

Fleet Management Limited is committed to diversity, equity and inclusion in the workplace. We prohibit discrimination and harassment of any kind based on race, color, sex, religion, sexual orientation, national origin, disability, genetic information, pregnancy, or any other protected characteristic as outlined by local laws.