An opportunity exists for an experienced Python Engineer to lead the design, development, and support of Python-based analytics applications, dashboards, and data products that drive business decision-making.
This role sits at the intersection of software engineering, data analytics, and stakeholder engagement, with a strong focus on building scalable applications, visualisation platforms, and analytical solutions for both technical and non-technical users.
Key Responsibilities
* Design, develop, and maintain Python-based applications, dashboards, and analytical tools.
* Build interactive visualisation solutions using technologies such as Dash, Streamlit, Power BI, or equivalent platforms.
* Develop scalable data pipelines and integrate data from multiple internal and external sources.
* Work closely with business stakeholders to translate complex requirements into intuitive analytical products.
* Establish best-practice software engineering standards including code quality, testing, documentation, and governance.
* Support cloud-based deployment and ongoing enhancement of analytics applications.
* Mentor team members and promote adoption of modern development practices across the organisation.
* Partner with data, technology, and business teams to deliver high-value analytical solutions.
Skills & Experience
* Strong commercial experience developing applications and analytical solutions using Python.
* Advanced knowledge of Python libraries including Pandas, NumPy, Plotly, Dash, Streamlit, and related frameworks.
* Experience building dashboards, reporting platforms, and data visualisation solutions.
* Strong understanding of software engineering principles, application architecture, and development best practices.
* Experience working with cloud platforms such as Azure and modern CI/CD practices.
* Familiarity with SQL, data warehousing, and large-scale data environments.
* Strong stakeholder engagement and communication skills with the ability to work across technical and non-technical teams.
* Experience mentoring developers and contributing to technical standards and governance.
* Experience within financial services, investments, quantitative analytics, or asset management environments.
* Exposure to Snowflake, Microsoft Fabric, Databricks, or PySpark.
* Experience deploying containerised applications using Docker and Kubernetes.
* Knowledge of investment analytics, portfolio reporting, performance measurement, or risk analytics.
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