Overview
We are seeking a Data Engineer to join a leading global investment organization on a 12-month contract, fully remote within the UK. In this role, you will be part of the Technology & Innovation function, collaborating with both technical teams and business stakeholders to build and enhance data pipelines, develop data models, and support AI-powered analytics applications. This position focuses on transforming complex data into structured solutions and improving data capabilities for investment and portfolio management teams.
Responsibilities
- Develop, maintain and enhance data pipelines using SQL, Python, and modern data engineering tools.
- Build and optimise data models to support financial analysis, investment reporting, and AI applications.
- Work with internal and external data sources, ensuring information is accurately extracted, cleaned, validated, and transformed.
- Use Snowflake, dbt, and Apache Airflow to support data warehousing, transformation, and orchestration.
- Partner directly with business stakeholders to understand complex data requirements and translate these into technical solutions.
- Develop transformation logic to address business challenges, including financial calculations, currencies, and data consistency.
- Take ownership of individual data workstreams within wider technology projects.
- Identify opportunities to improve data quality, processes, and existing solutions.
Requirements
- Strong SQL skills, including complex queries, joins, and window functions.
- Practical Python experience.
- Experience working with data pipelines, data transformation, and data modelling.
- Familiarity with modern data engineering technologies such as Snowflake, dbt, or Apache Airflow.
- Experience working with relational databases.
- Ability to understand business requirements and translate them into structured data solutions.
- Excellent communication skills, with the confidence to work directly with non-technical stakeholders.
- A proactive approach, strong analytical thinking, and the ability to take ownership of work independently.