Aspect Capital - Data Engineer

LGBT Great; London; On-site; GBP 50,000 - 70,000; Full time

Job summary

A leading data-focused hedge fund in London is seeking a Data Engineer to join its team. The role involves managing diverse datasets, utilizing technologies like Python and SQL, and collaborating with various stakeholders. The ideal candidate will have 1-3 years of experience and familiarity with DevOps tools. This position offers an exciting opportunity to influence data processing and technology enhancement.

Qualifications

• 1-3 years working as a Data Engineer.
• Understanding of core database concepts.
• Familiarity with cloud platforms or data warehouses.

Responsibilities

• Ingestion, storage, transformation, and distribution of datasets.
• Building streaming platforms for large volumes of tick data.
• Developing ELT pipelines to transform datasets.

Skills

Python

SQL

Communication with non-technical colleagues

DevOps

Monitoring

Automated testing

Tools

Git

Docker

Jenkins

dbt

Snowflake

Kafka

Airflow

Job description

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Aspect Capital

Aspect Capital is an award-winning systematic hedge fund based in London that manages over $8 billon of client assets, where technology is an integral part of the business. We are looking for an engineer to join our Data Engineering team. The team's role is broad, covering the ingestion, storage, transformation and distribution of tick, timeseries, reference and alternative datasets. The technology stack is similarly varied including a range of legacy and modern systems, across on-premises and cloud infrastructure.

This is an exciting time to join the team as we consolidate our technology estate, revamp how we process and filter data, and overhaul the way data is accessed by our consumers, while continuing to onboard new datasets that enhance our strategies. We are a lean team owning end-to-end delivery from initial design through to operational support in production.

• 1-3 years working as a Data Engineer
• Expertise with Python and SQL
• Understanding of core database concepts
• Familiarity with a cloud platform or data warehouse
• SDLC and DevOps: Git, Docker, Jenkins/TeamCity, monitoring, automated testing
• Ability to communicate clearly with technical and non-technical colleagues

Experience in the following areas would be ideal:

• dbt and Snowflake
• Kafka
• Airflow

• Building a streaming platform to capture and aggregate large volumes of tick data
• Developing ELT pipelines to ingest and transform datasets with Python, Snowflake and dbt
• Enhancing client libraries to provide unified access to our entire data catalogue
• Supporting our Java live data feedhandlers
• Consolidating legacy MATLAB systems onto our strategic technology stack
• Working closely with quantitative developers, researchers and portfolio managers

If you are passionate about technology, stay current with industry trends, follow engineering best practices, and are always looking for opportunities to improve systems, processes, and performance, then we would love to hear from you.

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