Company Insight:
A world-leading algorithmic trading business is looking to engage with a seasoned data-centric engineer to overhaul their in-house data platform designed for execution on a multi-PB scale, leveraging cutting-edge technology to trade hundreds of billions worth of assets per day.
You will design, build and implement end-to-end system architecture for an integral platform serving the entirety of front-office trading operations. You will partner closely with world-class Quant Research mathematicians and internal stakeholders, building scalable backend processes to ingest and transform vast quantities of data to execute manual trades, assess risk, and research improvements to complex strategies. The work 'is in-the-weeds' and architecturally nuanced, where design choices have immediate and lasting impact on performance.
This has real scope to shape system architecture and influence long-term technical direction in an organisation that gives voice to all technologists. Existing engineers at the firm relish the speed of implementation, lack of bureaucracy/politics and opportunity for commercial impact within a technologically autonomous setting.
Responsibilities:
* Develop scalable and efficient data and research infrastructure.
* Build fully automated pipelines to ingest and process third party data and make it available to internal users.
* Formulate new algorithmic approaches for improving the quality of the data (such as error correction), discover new patterns within the existing datasets, and source new datasets altogether.
* Implement workflows for processing both structured and unstructured financial datasets.
* Promptly and frequently communicate new updates to internal teams and stakeholders to aggregate and address incoming requests.
* Analyze dataset coverage and quality; create reusable data analysis libraries.
* Collaborate closely with trading and research teams to extend, optimise and utilise the data platform.
Requirements:
* Outstanding educational credentials in Computer Science, Mathematics, Statistics or other STEM discipline.
* Elite Proficiency in SQL, preferably PostgreSQL.
* Must be proficient in a statistically-typed language such as C++, Java or Rust.
* Professional Experience with Data Pipelines, ETL Tools and relational databases are all highly desirable.
* Comfortable with data analysis and statistics; required to ensure sufficiently clean data
* Experience building and maintaining distributed systems.
* Outstanding Experience in both using and administering relational databases will be highly beneficial in the role.
* Knowledge of finance and trading is not required but is highly beneficial.
* Personable and highly communicative - Will be collaborating with a diverse range of internal stakeholders.
* 2-6 years of experience in a data-driven software engineering role is ideal. Candidates with over 6 years of experience will likely not be considered.