In this Data Engineer role, you will design and maintain a scalable data platform to support advanced analytics and quantitative research. You will build robust data pipelines, enable real-time data feeds, and ensure smooth data flow for structured and unstructured data. You’ll optimize ingestion, enhance architecture, automate ETL, and support event-driven systems to enable fast data insights. Collaborate with analysts and researchers to meet data requirements and improve data accessibility and security. This is a data-driven, fast-paced environment where your expertise will directly impact decision making.
Responsibilities
Design and maintain high-performance data pipelines for large-scale datasets
Integrate real-time feeds and external APIs to optimise ingestion
Advance data architecture for accessibility, efficiency, and security
Automate ETL workflows to streamline data modelling and analysis
Support event-driven systems using Kafka and Protobuf for seamless streaming
Ensure data quality and consistency across inputs and outputs
Collaborate with analysts/researchers to prepare data for ML model training and deployment
Key requirements
3+ years of data engineering experience
Strong proficiency in Python and Rust
Hands-on experience with AWS, Linux, and Docker
Experience with distributed computing frameworks (Ray, Dask, or Apache Arrow)
Strong analytical skills for handling large-scale, high-frequency data
Solid understanding of ETL pipelines, data modelling, and database optimisation
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