**Data Engineer - Quantitative Hedge Fund**
* This is a rare opportunity for an experienced Data Engineer to join a leading Quantitative Hedge Fund.
The successful candidate will be responsible for designing and implementing data pipelines from major financial market data vendors, including Bloomberg, Refinitiv, Factset, and MorningStar. This will involve working with various technologies such as Python, SQL, dbt, Snowflake, and Databricks.
The team works on a hybrid schedule, with a minimum of three days per week in the office. The firm is renowned for its friendly, supportive, and collegiate culture, with an enviably low staff turnover.
Key Requirements:
1. 5+ years of experience as a Data Engineer, with at least 2 years in Financial Markets Engineering, especially in a Hedge Fund, Trading Firm, or Quant Trading Technology.
2. Expertise in Python and SQL, with familiarity with relational and time-series databases. Experience with Airflow, dbt, Snowflake, Databricks, or other Cloud Data Warehouses is highly desirable.
3. Implementing data pipelines from major financial market data vendors (Bloomberg, Refinitiv, Factset...).
4. Strong understanding of SDLC and DevOps practices, including Git, Docker, Jenkins/TeamCity, monitoring, testing, and agile methodologies.
5. Passionate about code quality, data integrity, and building scalable and robust systems.
6. Able to communicate clearly with technical and non-technical colleagues.
In this role, you will have the opportunity to work with a talented team of engineers, contribute to the development of cutting-edge data solutions, and help drive the success of the business.