BI Data Engineer

At Kpler, we are dedicated to helping our clients navigate complex markets with ease. By simplifying global trade information and providing valuable insights, we empower organisations to make informed decisions in commodities, energy, and maritime sectors.

Since our founding in 2014, we have focused on delivering top-tier intelligence through user-friendly platforms. Our team of over 700 experts from 35+ countries works tirelessly to transform intricate data into actionable strategies, ensuring our clients stay ahead in a dynamic market landscape. Join us to leverage cutting-edge innovation for impactful results and experience unparalleled support on your journey to success.

We are looking for an experienced and highly motivated Senior BI Data Engineer to join our Business Intelligence & Insights team and play a key role in shaping the data foundations that power Kpler’s products, analytics, and strategic decision-making. Reporting to the Director of BI, you will build scalable pipelines, robust data models, and reliable infrastructure that enable teams across the organisation to access accurate, high-quality data.

This is a high-impact role for someone who enjoys solving complex data problems, thrives in an international, fast-paced environment, and is excited to design the systems that fuel insights, reporting, and machine learning at scale.

• Architect and develop scalable, resilient, high-quality data solutions to support analytics, reporting, and machine learning workloads.
• Design, implement, and maintain reliable ETL/ELT pipelines that integrate, cleanse, and consolidate data from diverse internal and external sources, including APIs and third-party systems.
• Ensure data is accurately ingested, transformed, stored, and made accessible through robust testing frameworks and clearly defined business rules.
• Translate business requirements into scalable data models and transformation logic, working with large, multidimensional datasets to surface insights, trends, and opportunities.
• Build and maintain the BI reporting codebase, ensuring high standards of data integrity, availability, and performance across the organization.
• Create and maintain backend infrastructure that supports analytics platforms, dashboards, and machine learning pipelines.
• Develop and execute unit and integration tests for data pipelines and transformation scripts to ensure reliability and consistency.
• Proactively identify inefficiencies and bottlenecks in data flows and propose scalable, forward-looking solutions.
• Partner closely with product managers, engineers, commercial teams, and business stakeholders to understand strategy and data needs, aligning delivery with the BI roadmap.
• Contribute to team growth through code reviews, design discussions, and knowledge sharing, while staying current with industry best practices.
• Take ownership of the quality, integrity, and consistency of the BI data codebase and associated datasets.
• Ensure ETL efficiency and data availability to meet stakeholder requirements and business SLAs.
• Adhere to engineering best practices, including documentation, version control, and maintainable code standards.
• Support and deliver against team OKRs and KPIs, contributing to overall team and business success.

• 4+ years of back-end and/or data engineering experience, delivering production-grade data solutions.
• Demonstrated experience working in a global or international environment, collaborating across regions and time zones.
• Strong SQL expertise with hands-on Python scripting experience for data extraction, transformation, and analysis.
• Proven experience ingesting and processing data from external APIs and third-party data sources.
• Strong experience working with AWS cloud infrastructure, including EKS and ECS, and with modern data warehousing solutions (ideally Big Query).
• Solid understanding of BI data architecture, with experience using version control systems such as Git Hub or Git Lab.
• Demonstrated ability to understand business logic behind datasets, ensuring high standards of data quality, consistency, and trust.
• Highly analytical and detail-oriented, with a focus on building…