Data & AI Engineer

The Role

You will design, build, and evolve the data foundations of our SaaS platform with a clear focus on long‑term AI readiness. The role ensures that financial and operational data is captured, structured, governed, and maintained in a way that supports reporting, integrations, decision support, and future AI and automation use cases. This role sits at the intersection of data architecture, data engineering, and AI enablement. While initial responsibilities focus on core data foundations, the role will increasingly support AI use cases such as intelligent automation, advanced analytics, and AI‑driven decision support.

What You’ll Do

• Build and evolve the core data architecture and relational data models (databases, tables, relationships) for financial and operational domains (costs, expenses, budgets, invoices, and workflows).
• Build and maintain data integrations and pipelines between internal services and external systems to support reporting, analytics, and future AI use cases.
• Ensure data quality, consistency, and traceability through clear definitions, documented assumptions, and maintainable data flows.
• Structure and prepare data for AI and advanced analytics use cases, such as classification, validation, similarity search, and recommendations.
• Collaborate closely with product and engineering teams to translate business and AI requirements into robust data structures.

What We’re Looking For

Required:

• Solid hands-on experience with databases and structured data design (SQL, schema design, joins, constraints, indexes, query performance basics).
• Practical experience with relational data modeling (entities, relationships, normalization/denormalization trade-offs).
• Working knowledge of data quality practices (validation, consistency checks, monitoring, and debugging data issues).
• Experience building or supporting data integrations / backend data workflows (e.g., service-to-service data flows, ETL/ELT-style movement, APIs).
• Ability to prepare and structure data for analytics/AI consumption (clean, well-labeled/defined fields, consistent history, reproducible transformations).
• Ability to work cross-functionally with product, engineering, and business stakeholders to clarify requirements and deliver maintainable solutions.
• English communication skills (both written and verbal).

Nice to have:

• Experience working with financial/accounting and operational data domains, ideally in maritime, logistics, industrial, or similar environments.
• Exposure to analytics and AI/ML use cases (e.g., feature-ready datasets, labeling, evaluation datasets, vector search)
• Experience working on SaaS platforms.
• Bachelor’s degree in computer science, Engineering, or a related field.
• Familiarity with performance measurement concepts, KPIs, dashboards, and operational reporting.

Our Culture

• Innovative thinking with thorough execution
• High attention to detail
• Independence combined with strong teamwork
• A drive to be part of meaningful change