Data Engineer​/Analytics Engineer - Aftermarket Sales

1. Role Purpose

We want to improve and extend the usage of data in our decision making by creating a robust, scalable data foundation for Aftermarket Sales and related functions. The ultimate goal is to ensure high-quality, consistent, and reliable data that enables accurate analysis, better prioritization, and increased sales.

As an Analytics Engineer – Aftermarket Sales, you will play a key role in integrating data from diverse systems, including legacy and modern platforms, and in building data models and pipelines that ensure data quality and consistency. You will contribute to our long-term data strategy and help define best practices for data collection, storage, and processing.

• Collect, integrate, and transform data from multiple disparate systems (legacy and modern) into structured, analytics-ready datasets.
• Identify and address data quality issues (missing data, inconsistencies, duplicates), and implement robust data cleaning and validation processes.
• Design, build, and maintain data pipelines (ETL/ELT) that feed analytical and reporting environments.
• Develop and maintain data models (e.g. dimensional models, star schemas, semantic layers) that provide a consistent view of aftermarket and commercial data.
• Recommend and implement improvements to data collection, storage, and processing to support both current and future analytical needs.
• Support the creation and implementation of a long-term data strategy, ensuring scalable and sustainable data architectures for the company.
• Collaborate closely with data analysts, business stakeholders, and IT/engineering teams to understand data requirements and translate them into technical solutions.
• Contribute to the definition and implementation of data governance practices, including documentation, metadata, and data lineage.
• Ensure that data infrastructure and pipelines are secure, reliable, and performant.

• Proven experience as an Analytics Engineer, Data Engineer, BI Engineer, or similar role working with analytical data environments.
• Strong proficiency in SQL, including experience with complex queries, performance optimization, and data modeling.
• Experience with at least one programming language used for data engineering, such as Python (preferred) or similar.
• Solid understanding of data integration, cleaning, and validation techniques at scale.
• Experience working with data from multiple legacy systems and modern platforms.
• Understanding of data warehousing or data lake solutions (cloud or on-premises).
• Familiarity with data governance and best practices in setting up and maintaining data pipelines.
• Ability to work closely with both technical and business teams, understanding their data needs and constraints.

• Experience in maritime, logistics, manufacturing, or other asset-heavy industries.
• Experience with orchestration and transformation tools (e.g., Airflow, dbt, or similar – depending on your tech stack).
• Experience designing semantic layers or data models specifically to support BI tools (Power BI, Tableau, Qlik, etc.).

• Opportunity to shape the data foundation and strategy of a leading maritime company.
• Work on a wide variety of products, assets, and systems, both new and legacy.
• A collaborative environment, working closely with business and analytics teams, with direct impact on how decisions are made.
• Competitive salary and benefits package.