Finance Data Developer (6-Month Contract)

atlascorp

18d • $80,000 - $95,000

About The Position

Seaspan employees are goal-driven and thrive in a high-performance culture. Our integrated business model, with over 25 years of fleet life-cycle management expertise, provides the world’s major shipping companies with long-term leases on large, modern and technologically advanced vessels, combined with industry-leading ship management services. As owner and operator of the vessels, we provide skilled officers and crews dedicated to the safe, reliable, and economical operation of our fleet. Seaspan's fleet has evolved over time to meet the varying needs of our customer base. We own vessels in a wide range of sizes, from 2,500 TEU to 24,000 TEU. Our main operating offices are located in Singapore, Vancouver, Hong Kong, and Mumbai.

The Business Intelligence department is responsible for enabling the Enterprise Data & Analytics Strategy across the organization by providing unified approaches, tools, and standards for all facets of Seaspan’s data management and consumption. Within this department, the Finance Intelligence Team works in close partnership with Finance, Business Development, and Technology functions to support data-driven decision-making and digital transformation initiatives.

The Finance Data Developer will play a key role in designing and implementing scalable financial logic and analytical capabilities across systems. This role focuses on translating complex financial models into structured, reusable technical components, enabling improved data consistency, enhanced valuation capabilities, and integration of finance logic into enterprise data platforms and emerging AI solutions.

Requirements

• Bachelor’s degree in Computer Science, Engineering, Information Systems, Finance, Accounting, Economics, or a related field.
• A minimum of 3–5 years of professional experience in software development, data engineering, or related technical roles; experience supporting finance, financial systems, or analytics use cases is preferred.
• Strong understanding of corporate finance concepts, including financial reporting, cashflow analysis, liquidity management, and valuation methodologies.
• Proficiency in Python for financial modeling, data processing, and logic implementation.
• Experience working with data platforms such as Databricks, PySpark, or similar data processing frameworks is preferred.
• Understanding data pipelines, data structures, and system integration concepts.
• Ability to translate complex financial concepts into structured, scalable technical solutions.
• Strong analytical and problem-solving skills with high attention to detail and data accuracy.
• Strong communication and documentation skills, with the ability to collaborate across Finance, Commercial, and Technology teams.
• Self-starter capable of working independently and driving solutions in a fast-paced environment.

Nice To Haves

• Experience building financial models, valuation tools, or scenario analysis applications.
• Experience with data platforms such as Databricks, PySpark, or similar big data environments.
• Familiarity with data visualization tools (e.g., Power BI, Plotly Dash) and interactive UI design principles.
• Understanding of data governance, documentation standards, and best practices in software and data development.
• Exposure to AI/ML applications or experience building structured logic for automation or AI integration.

Responsibilities

• Design and implement centralized financial calculation logic (e.g., revenue, cashflow, liquidity, valuation) as modular, reusable components into an existing coding library.
• Translate complex financial models and business requirements into technical specifications, including data pipelines, data models, and transformation logic.
• Support development of scalable valuation tools for deal evaluation, scenario modeling, and financial analysis in collaboration with Business Development teams.
• Collaborate with Data Scientists, Data Operations, and BI teams to integrate financial logic into enterprise platforms (e.g., Databricks, EDW, data lake).
• Develop structured, callable financial functions to support Finance AI Agent capabilities and ensure alignment between business logic and AI-driven outputs.
• Validate and reconcile financial data and calculations across systems to ensure consistency, accuracy, and reliability.
• Identify and resolve discrepancies between financial models, source systems, and reporting outputs.
• Establish and maintain high level of documentation, coding standards, and governance practices for financial logic in collaboration with Data Governance teams.
• Support data quality improvement initiatives by standardizing financial definitions, assumptions, and calculation methodologies.

What This Job Offers

• Career Level: Mid Level