Software Engineer - Data
Posted 4 days ago by Aspect Capital
Negotiable
Undetermined
Undetermined
London, England, United Kingdom
Summary: Aspect Capital is seeking a senior engineer to join their Data Engineering team, which is responsible for the ingestion, storage, transformation, and distribution of various datasets. The role involves working with a diverse technology stack, including both legacy and modern systems, and offers the opportunity to enhance data processing and access methods. The ideal candidate will have a strong background in software or data engineering, particularly with Python or Java, and experience in the financial industry. This position is pivotal as the team consolidates its technology estate and integrates new datasets to improve strategies.
Key Responsibilities:
- Ingest, store, transform, and distribute tick, timeseries, reference, and alternative datasets.
- Work with a range of legacy and modern systems across on-premises and cloud infrastructure.
- Revamp data processing and filtering methods.
- Overhaul data access for consumers and onboard new datasets.
- Own end-to-end delivery from initial design to operational support in production.
- Develop ELT pipelines to ingest and transform datasets using Python, Snowflake, and dbt.
- Build a streaming platform for capturing and aggregating tick data.
- Support Java live data feed handlers and consolidate legacy MATLAB systems onto a cloud-native technology stack.
- Collaborate with quantitative developers, researchers, and portfolio managers.
Key Skills:
- 2-4 years of experience as a Software Engineer or Data Engineer.
- Strong expertise in Python or Java.
- Well-versed in SQL and understanding of relational databases or data warehouses.
- Clear communication skills with technical and non-technical colleagues.
- Experience in the financial industry.
- Familiarity with Snowflake and dbt.
- Knowledge of major financial data vendor APIs, Kafka, AWS, and Airflow.
- Experience in developing ELT pipelines and building streaming platforms.
- Ability to extend internal libraries for unified data access.
Salary (Rate): undetermined
City: London
Country: United Kingdom
Working Arrangements: undetermined
IR35 Status: undetermined
Seniority Level: Senior
Industry: IT
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 teams 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. We're seeking an individual who is passionate about technology, stays current with industry trends, follows engineering best practices, and is always looking for opportunities to improve systems, processes, and performance.
2-4 years working as a Software Engineer or Data Engineer Strong expertise with Python or Java Well-versed in SQL and a good understanding of relational databases or data warehouses Ability to communicate clearly with technical and non-technical colleagues Financial industry experience Experience In The Following Areas Would Be Ideal Snowflake and dbt Familiar with major financial data vendor APIs Kafka AWS Airflow Developing ELT pipelines to ingest and transform datasets with Python, Snowflake and dbt Building a streaming platform to capture and aggregate large volumes of tick data Extending internal libraries to provide unified access to our entire data catalogue Supporting our Java live data feedhandlers Consolidating legacy MATLAB systems onto our cloud-native 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.