Senior Lead, Software Engineering

Tasks

- The Sr. Lead will work closely with portfolio managers, traders, and front-office technology teams to deliver high-quality solutions in the areas of portfolio management and ETF technology. This role acts as a critical liaison between investment stakeholders and agile engineering teams, translating complex investment workflows into clear, actionable business and functional requirements. - Interpersonal skills: Strong interpersonal skills, collaboration with quants, portfolio managers, and business stakeholders. - Proven ability to lead cross-functional teams and influence strategic decisions.

Agile Delivery & Execution

- Collaborate with agile teams to drive delivery through backlog refinement, sprint planning, demos, and retrospectives. - Create and maintain user stories, UAT scenarios, release notes, and supporting documentation. Coordinate and execute user acceptance testing (UAT) with business users and technology partners. - Serve as the single point of contact between business and technology to ensure alignment on scope, priorities, and outcomes. - Clearly communicate trade-offs, risks, and dependencies to senior investment and technology stakeholders. - Work closely with partners and contractors overseas to deliver solutions and improve productivity using AI tools such as Github Copilot.

Data Engineering & Management

- Design and optimize complex SQL queries, stored procedures, and data models for performance and scalability. - Integrate data pipelines and ETL processes using Python and Azure Data Factory or similar tools. - Collaborating with product managers, business analysts, and stakeholders to translate business requirements into technical specifications. - Planning and executing agile ceremonies (sprint planning, retrospectives, daily stand-ups) and contributing to backlog maintenance and story estimation.

Requirements

- Strong interpersonal skills - Proven ability to lead cross-functional teams and influence strategic decisions - Experience with agile methods and tools

Domain knowledge (desirable)

- Understanding of asset management investments and asset classes (equities, fixed income)

Training and skills (Desirable)

• Databases: RDBMS (SQL Server, PostgreSQL, or MySQL)
• Cloud: Microsoft Azure (App Services, Functions, Key Vault, Azure SQL, Blob Storage, Azure DevOps)
• Languages: Python, SQL (T-SQL, PL/SQL), C(.Net), and Bash
• Data tools: Azure Data Factory, Pandas, NumPy, PySpark
• Testing: PyTest, other Python or .Net unit test and integration test frameworks
• Monitoring: Application Insights, Azure Monitor, Log Analytics

We offer

- A comprehensive salary package - A comprehensive benefits package that offers a rewarding and fulfilling experience - A flexible and collaborative work culture - A work environment with a greater purpose - The opportunity to be part of one of the world's most admired and sustainable companies