Lead Data Analyst (Global Liner Shipping)

Job Purpose

• We are seeking a technically sophisticated and experienced Lead Data Analyst to drive data-driven decision-making within our Global Container Shipping division.
• In this pivotal role, she/he will act as the bridge between complex maritime operations and advanced data analytics. She/he will be responsible for architecting scalable data models in Google BigQuery, developing semantic layers in Looker, and leading a team of analysts to uncover insights related to fleet utilization, yield management, trade lane performance, and logistics optimization.
• This is a hands-on technical leadership role. She/He is expected to write complex production-level SQL, govern LookML codebases, and mentor junior analysts on best practices.

Primary Job Description (Describe the major duties of this position)

1. Technical Leadership & Data Strategy

• Lead, mentor, and review the work of a team of data analysts, ensuring high standards of code quality, query performance, and data accuracy.

• Establish best practices for SQL coding standards, version control (Git), and data documentation within the analytics team.

• Translate high-level business requirements from Commercial, Operations, and Logistics stakeholders into technical data specifications.

2. Advanced Analytics & Engineering (BigQuery)

• Design and execute complex, optimized SQL queries within Google BigQuery to handle huge scale shipping data (AIS data, bookings, bills of lading, equipment moves).

• Perform data modeling and transformation to prepare datasets for BI consumption, ensuring cost-efficiency and query performance in BigQuery.

• Investigate data discrepancies and work closely with Data Engineers to resolve pipeline issues.

3. Business Intelligence & Semantic Modeling (Looker)

• Serve as the primary owner of the Looker instance and LookML project.

• Architect and maintain efficient LookML models (views, explores, joins) to ensure a "single source of truth" for key shipping KPIs (e.g., Load Factor, Net Yield/TEU, Schedule Reliability, Detention & Demurrage).

• Design intuitive, high-performance dashboards that enable real-time monitoring of vessel performance and cargo flow.

4. Domain-Specific Analysis

• Conduct deep-dive analyses on profitability by Trade Lane, Service Loop, and Customer segments.

• Analyze container flow imbalances and empty repositioning costs to suggest optimization strategies.

• Monitor vessel schedule integrity and port congestion impacts using historical and real-time data.
  

  Position Qualifications and Experiences

  Experience

  • 5+ years of professional experience as a Data Analyst, Data Engineer, or Analytics Engineer.

  • Minimum 5 years of direct experience in the Maritime / Global Container Shipping industry. (Must understand concepts like Bills of Lading, TEU, Voyage/Leg, Port Pairs, Demurrage, Bunker consumption, etc.)

  Technical Skills (Must-Have)

  • Expert-level SQL proficiency: Ability to write window functions, complex joins, nested fields handling, and query optimization specifically for Google BigQuery.

  • Deep expertise in Looker: Proven experience in developing and managing LookML models and user permissions (not just building dashboards via UI).

  • Experience with version control systems (Git/GitHub/GitLab).

  Soft Skills & Leadership

  • Proven track record of leading projects or mentoring junior team members.

  • Ability to explain complex technical concepts to non-technical stakeholders (e.g., Line Managers, Trade Managers).

  • Strong problem-solving skills and attention to detail.

  Preferred Qualifications (Nice to have)

  • Experience with dbt (data build tool) for data transformation.

  • Proficiency in Python or R for advanced statistical analysis or forecasting.

  • Experience with Google Cloud Platform (GCP) ecosystem beyond BigQuery (e.g., Cloud Composer/Airflow, Cloud Functions).

  • Knowledge of supply chain logistics beyond port-to-port (e.g., intermodal/inland logistics).

  Tech Stack

  • Data Warehouse: Google BigQuery

  • BI & Visualization: Looker (LookML)

  • Version Control: Git

  • Transformation: SQL (Standard), dbt (preferred)