Data Engineer - BDA

Description

The company is a global quantitative and systematic investment manager trading across all liquid asset classes, and it applies scientific methods to investing using data and technology.

The Business Data & Analytics team builds applications and business insights for senior stakeholders, backed by a data platform that supports those applications, analytical tools, data science, analysis and applied AI.

We are hiring a Data Engineer to help build and maintain the BDA data platform. You will work directly with business stakeholders, turning open-ended questions into reliable datasets, analyses and tools.

Responsibilities

• Design, build and operate data pipelines and datasets on AWS, using S3, Lambda, Step Functions, Glue and Athena.
• Define infrastructure as code and ship changes through CI/CD.
• Bring together internal and external data sources, checking their quality and reliability.
• Build reporting and BI views and present findings to non-technical stakeholders.
• Use agentic coding tools in daily development, and design data and systems that AI agents can use safely.
• Help develop LLM-based projects covering document extraction, natural-language access to data and automated data quality.
• Share ownership of the team's systems, recording design decisions, assumptions and limitations.

Requirements

• A degree in Computer Science, Engineering, Mathematics, Statistics or another relevant technical field.
• At least 3 years of experience building and running production data pipelines and datasets.
• Strong hands-on experience with AWS, including IAM.
• Strong Python and SQL skills, with clean, structured and tested code.
• Experience with infrastructure as code and agentic coding tools, including reviewing and verifying their output.
• Strong analytical and problem-solving skills, intellectual curiosity and a consulting mindset.
• A proactive, organised and versatile approach, with interest in BI, analysis and data science as well as engineering.
• Comfortable working on problems whose requirements are not fully defined.
• Desirable: experience with, or a willingness to learn, Terraform.
• Desirable: experience with, or a willingness to learn, Dash, FastAPI or similar frameworks for dashboards, reporting and data applications.
• Desirable: experience with, or a willingness to learn, LLMs, including agents, tool use, retrieval or MCP.
• Desirable: experience with, or a willingness to learn, AI-friendly data architectures, including machine-readable data contracts, catalogues and metadata.
• Desirable: experience with, or a willingness to learn, applying machine learning or statistical methods to business problems.
• Desirable: experience with, or a willingness to learn, Spark or PySpark.

Conditions

The company is an equal opportunity employer that values diversity.

Benefits

• The company offers initiatives and programmes to support a healthy work-life balance.