Teams at Quilter

Measures and attributes investment performance across client and model portfolios. Maintains model and benchmark data, produces performance and attribution reports, investigates anomalies and data-quality issues, and supports investment managers, research teams, committees, and investment risk. The role also improves performance processes, develops internal systems and procedures, responds to ad hoc analysis requests, and presents performance findings.

Designs, develops, tests, deploys, and supports scalable data pipelines, integrations, and data products on Quilter’s Azure-based platform. The role uses Databricks, Azure Data Factory, Data Lake Storage, Spark, and related technologies to support analytics, reporting, regulatory, and operational needs. Responsibilities include data governance, security, quality, CI/CD, monitoring, incident resolution, performance optimization, and stakeholder collaboration within Agile teams.

Lead technical design and delivery of scalable data platforms, pipelines, data products, and engineering standards. The role requires hands-on Databricks and Azure expertise across batch and streaming architectures, data governance, modelling, security, observability, CI/CD, and infrastructure automation. It also involves mentoring engineers, reviewing architecture and code, resolving complex technical issues, collaborating with architects and stakeholders, and improving data quality, reliability, and platform performance.