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Data Engineer - Snowflake | DBT | Python - Investment Management - Strike IT

Strike ITLondon🇬🇧United KingdomPosted 20 Jul 2026

Why This Role Stands Out

This hybrid role offers a fantastic chance to enhance your skills with Snowflake, DBT, and Python within a reputable investment management firm, contributing to critical business functions. If you thrive on solving complex data challenges and collaborating in a dynamic Agile environment, this opportunity is ideal for you to grow your career. Apply now to join a highly collaborative team and make a significant impact!

Quick Overview

Work Type
Hybrid
Schedule
Full Time
Level
Mid Senior

Job Description

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

Skills

SQL
SQL Server
ETL
Snowflake
Agile
Azure
Databricks
Git
Power BI
Python
dbt

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