Senior Data Engineer building large-scale investment data and analytics platforms for a global investment fund in Singapore, working closely with investment, trading, ops and risk teams. The stack centers on Databricks, Python, PySpark, SparkSQL, SQL, DBT and Airflow on AWS, plus Docker, Kubernetes, Terraform and CI/CD.
Senior Data Engineer (DATABRICKS & AWS) | Global Investment Fund | Singapore
We're working with one of the world's largest and most sophisticated
global investment funds
on a senior hire within their Data Engineering team in Singapore.
This is an opportunity to work on
large-scale investment data and analytics platforms
that are used directly by investment professionals and technology teams across the organisation. Rather than sitting in a purely backend data function, you'll get significant exposure to the investment business and help shape how data is consumed across asset management, trading, investment operations and risk.
The technology environment is modern and heavily focused around
Databricks
, Python, PySpark, SparkSQL, SQL, DBT and Airflow, alongside AWS cloud-native technologies. You'll be building and evolving enterprise-grade data platforms, working across data transformation, modelling, architecture and analytics while helping the organisation continue to modernise its data infrastructure.
Hence, solid Databricks and AWS experience is ESSENTIAL.
There's also a strong engineering component to the position. You'll be working with
Docker, Kubernetes, Terraform, CI/CD and modern DevOps practices,
with responsibility for designing systems that are scalable, reliable and built to a high engineering standard.
They're looking for someone with around
8+ years of hands-on Data Engineering experience
who is still technically strong but can also operate at a senior level.
If this sounds relevant, feel free to apply to this ad or reach out directly at (HIDDEN TEXT) for a confidential discussion.