Equities Derivatives Risk & PnL — End-to-end ownership of built microservices: requirements/business understanding, development, testing, release/deployment, and production support

Tech stack

• Languages: Java 21/24, Python, TypeScript, SQL (BigQuery), Shell/Bash Scripting

• Java stack: Spring Boot, some Spring WebFlux / Project Reactor (Mono/Flux), REST APIs, authentication & security, Swagger/OpenAPI, JUnit, Maven

• Orchestration / workflows: Apache Airflow (DAG/config changes, multi-environment behaviour, monitoring)

• Cloud: GCP, BigQuery, Dataflow, Apache Beam, Google Cloud Storage (GCS)

• CI/CD: Jenkins (pipelines/Jenkinsfiles), automated deployments, build/image scanning

• Infrastructure as Code: Terraform (VMs/resources, automated provisioning via pipeline)

• Automation & delivery ops: Jira, Jira API automation, Git-managed change flows

• Dev tools / OS: IntelliJ, VS Code, Git; macOS, Linux, Windows

• Security & training: Secure Code Warrior; HSBC/GCP internal training; GitHub Copilot adopted for routine engineering tasks (boilerplate/refactors/testing) while keeping review/testing controls

Cross-team contribution: worked with the Global Head of Market Data and stakeholders worldwide to reduce external vendor debt from £4.5m to ~£2m

• Statistical programming across a high volume of studies (incl. oncology) for major pharma sponsors (e.g., Bayer): ADaM builds + TFL production for US FDA-facing deliverables, including survival analysis (Kaplan–Meier curves/plots with confidence intervals) and inferential outputs (t-tests, chi-square); extensive QC/validation.

• Accelerated progression to statistical programming lead responsibilities; supported other programmers and communicated results to senior stakeholders.

• Supported statistical/ML analysis related to the Roadsaver™ carotid artery stent clinical evidence trial (missing data, event-rate analysis, survival methods)

• Collaborated with cross-site statisticians (Belgium/Japan) to deliver reproducible analysis in Python