Senior Data Engineer - ELT, Streaming & Cloud (Python)

Aspect Capital Limited; Greater London; On-site; GBP 90,000 - 125,000; Full time

Benefits offered by this job

Bonus

Medical Insurance

Electric car scheme

Flexi-working

Cycle to work scheme

Family Friendly Policies

Job summary

Aspect Capital Limited, a London-based hedge fund, seeks a senior data engineer to join the Data Engineering team. You will own end-to-end data processing, from ingestion to consumption, across tick, timeseries, reference, and alternative datasets.

You will shape the tech estate, improve data access, and onboard new datasets, collaborating with quantitative developers, researchers and portfolio managers. A strong background in Python, SQL, and cloud data platforms is essential.

Qualifications

• 5+ years as Software Engineer or Data Engineer.
• Strong Python skills.
• Strong SQL and relational DB knowledge.
• Proficient with Linux and Docker.
• Excellent communicator with both technical and non-technical colleagues.
• Financial industry experience.
• Experience with Java.
• Familiar with dbt, Snowflake and cloud data warehouses.
• Experience with Kafka and AWS.
• Familiar with major financial data vendor APIs.

Responsibilities

• 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 data catalogue.
• Consolidating legacy MATLAB systems onto our cloud-native technology stack.
• Working closely with quantitative developers, researchers and portfolio managers.

Skills

Python

SQL

Java

Linux

Docker

Communication

Financial experience

Tools

dbt

Snowflake

Kafka

AWS

Job description

Aspect Capital Limited, a London-based hedge fund, seeks a senior data engineer to join the Data Engineering team. You will own end-to-end data processing, from ingestion to consumption, across tick, timeseries, reference, and alternative datasets.

You will shape the tech estate, improve data access, and onboard new datasets, collaborating with quantitative developers, researchers and portfolio managers. A strong background in Python, SQL, and cloud data platforms is essential.