Software Engineering Lead – Data & Analytics Platforms (Hybrid)
We’re seeking someone to join our team as a Software Engineering Lead – Data & Analytics Platforms in Finance Technology to drive the architecture and delivery of scalable finance technology platforms while leading a high-performing team and advancing cloud data, reporting, and GenAI capabilities across the development lifecycle.
What you’ll do in the role
- Lead the architecture, design, and delivery of scalable, enterprise‑grade software systems using Java and/or Python, Angular and/or React, and other modern technologies, ensuring best practices in code quality, performance, and SDLC.
- Drive the design and integration of cloud-based data, reporting, and analytics solutions (preferably Snowflake), including scalable data pipelines and ETL.
- Champion the adoption of GenAI, LLMs, and Copilot‑style AI tooling to enhance developer productivity, automation, reporting, and intelligent data distribution.
- Provide technical leadership and mentorship to a high‑performing engineering team, fostering a culture of technical excellence, innovation, collaboration, and continuous learning.
- Partner with business stakeholders, product owners, and cross‑functional teams to define strategy and requirements, evaluate tools, and deliver solutions aligned with organizational goals.
- Champion modern SDLC practices – automated testing, CI/CD, and agile delivery – to ensure high‑quality, scalable, and maintainable solutions.
- Drive automation, code quality, data quality, and engineering best practices across all systems and pipelines.
- Ensure robust governance, security, and compliance throughout the software and data lifecycle.
What you’ll bring to the role
- 10+ years in software engineering, including substantial data‑platform experience, with a proven track record of delivering enterprise‑level solutions.
- Deep full‑stack expertise (Java and/or Python, Angular and/or React, and related technologies) with a strong command of data structures, algorithms, design patterns, and modern SDLC.
- Proven experience building and scaling enterprise applications in cloud environments.
- Strong hands‑on data engineering capability: SQL, data modelling, ETL, and scalable pipelines, ideally on a cloud data platform such as Snowflake.
- Proficiency across additional languages and frameworks, and the ability to learn new stacks quickly.
- Demonstrated experience leveraging GenAI, LLMs, or Copilot style tools for software development, automation, reporting, or analytics.
All positions are located in Montreal, Quebec. We offer a hybrid work environment, combining remote work and attendance in the office.
Knowledge of French and English is required.
Morgan Stanley is an equal opportunity employer committed to building and maintaining a workforce that is diverse in experience and background. Our recruiting efforts reflect our strong commitment to a culture of inclusion, where individuals are hired, developed, and advanced based on their skills and talents.
Our workforce reflects a broad cross‑section of the global communities in which we operate, bringing a variety of backgrounds, talents, perspectives, and experiences.
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