Data Engineer - Investment Management - Snowflake | DBT | Python

Contract: 4-month Initial Contract (Likely Extension)

Location: London (Hybrid Working)

IR35 Status: Inside IR35

An exciting opportunity has arisen for an experienced Data Engineer to join the technology team of a leading investment management organisation.

Working within a highly collaborative Agile environment, you'll play a key role in designing, developing and enhancing modern cloud-based data solutions that support front-office investment teams and critical business functions.

This is an excellent opportunity to work on a modern Azure and Snowflake data platform, helping to deliver scalable data pipelines, analytics capabilities and business-critical integrations.

The Role

You'll work closely with Business Analysts, Developers, Testers and business stakeholders to design and deliver high-quality data engineering solutions.

This role combines hands-on engineering with stakeholder engagement and requires someone who enjoys solving complex data challenges within a fast-paced investment management environment.

Key Responsibilities

1. Design, build and maintain scalable data pipelines and ETL/ELT solutions
2. Develop robust data models and transformations using Snowflake and dbt
3. Build and optimise data integrations across multiple platforms and applications
4. Work with Azure Data Factory and Databricks to develop modern cloud data solutions
5. Develop Python-based automation and data processing solutions
6. Write high-performance SQL for data extraction, transformation and reporting
7. Work alongside Business Analysts to translate business requirements into technical solutions
8. Participate throughout the full software development lifecycle
9. Perform testing and support business user acceptance
10. Ensure data quality, governance and best engineering practices are followed
11. Contribute to continuous improvement of the data platform and engineering standards

Experience:

We're looking for an experienced Data Engineer with strong cloud data engineering expertise, ideally gained within Financial Services or Asset Management.

You should have strong experience with:

1. Snowflake (essential)
2. dbt for data transformation (essential)
3. Python
4. Azure Data Factory
5. Azure Databricks
6. SQL Server
7. Advanced SQL development
8. ETL / ELT pipeline development
9. Cloud-based data engineering
10. Data modelling
11. API and data integration
12. Git and Agile delivery methodologies
13. Full software development lifecycle

Experience within investment management or financial services, including exposure to one or more of the following:

1. Front Office or Investment platforms
2. Asset Management
3. Market or reference data
4. ESG / Sustainability data
5. Bloomberg Aladdin or Aladdin Data Cloud (ADC)
6. Power BI
7. Web scraping
8. Enterprise scheduling tools such as JAMS