Data Engineer – Build Scalable Data Platforms

About the role

We are building a data platform that powers an AI system capable of translating global events into business forecasts. As a Data Engineer you will design, implement and maintain the data infrastructure that enables our forecasting models and customer‑facing products.

Key responsibilities

• Build and maintain reliable pipelines for structured and unstructured data.
• Integrate data from APIs, databases, files and external providers.
• Transform raw data into consistent, documented, and usable datasets.
• Develop systems for processing large‑scale temporal and economic data.
• Monitor pipeline performance, data freshness and quality.
• Investigate and resolve data inconsistencies, failures and performance issues.
• Collaborate with ML engineers to make data available for model training and inference.
• Work with product and software engineers to serve data through internal systems, APIs and customer‑facing products.
• Improve scalability, reliability and maintainability of the data platform.
• Contribute to data architecture, engineering standards and technical documentation.
• Automate manual data‑ingestion and validation processes.

Required profile

• Professional experience in data engineering or a closely related role.
• Strong Python and SQL skills.
• Experience building and maintaining production data pipelines.
• Familiarity with relational databases, data warehouses or data lakes.
• Understanding of data modelling, schema design and software‑engineering fundamentals.
• Ability to investigate data‑quality problems and trace issues across a pipeline.
• Comfortable working independently while knowing when to ask for help.

Required skills

• Python
• SQL
• Relational databases
• Data warehouses
• Data lakes
• Workflow orchestration tools
• Data‑transformation tools
• Data modelling
• Schema design
• APIs and external data sources