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Senior Data Engineer

Aspect Capital

London

On-site

USD 60,000 - 100,000

Full time

30+ days ago

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An established industry player is seeking a senior engineer to join their dynamic Data Engineering team. This role offers an exciting opportunity to work with cutting-edge technologies in a collaborative environment, where you'll be responsible for building and enhancing a KDB platform that captures vast amounts of tick data. You'll develop ELT pipelines using Python and Snowflake, and play a key role in consolidating legacy systems onto a strategic tech stack. If you're passionate about data integrity and scalable systems, this position is perfect for you to make a significant impact in a forward-thinking company.

5+ years as a data engineer or KDB developer with strong Python and SQL skills.
Experience with data pipelines from financial market data vendors.

Build and enhance the KDB platform for tick data aggregation.
Develop ELT pipelines to transform datasets with Python and Snowflake.

Python

SQL

Data Engineering

KDB Development

Data Pipelines

Agile Practices

Code Quality

Data Integrity

Communication Skills

Git

Docker

Jenkins

TeamCity

Snowflake

dbt

MATLAB

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Job description

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 a senior 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 for you 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.

Job requirements

Your experience:

5+ years working as a data engineer or KDB developer
Proficiency in Python and SQL and familiarity with relational and time-series databases
Experience implementing data pipelines, ideally from major financial market data vendors
SDLC and DevOps: Git, Docker, Jenkins/TeamCity, monitoring, testing, agile practices
Passionate about code quality, data integrity, and building scalable and robust systems
Ability to communicate clearly with technical and non-technical colleagues

Job responsibilities

Working closely with quantitative developers, researchers and portfolio managers you will:

Build and enhance our KDB platform to capture and aggregate large volumes of tick data
Develop ELT pipelines to ingest and transform datasets with Python, Snowflake and dbt
Extend Python libraries to provide unified access to our entire data catalogue
Support our Java live data feedhandlers
Consolidate legacy MATLAB systems onto our strategic technology stack

If this role sounds of interest we would love to hear from you.

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