We’re seeking someone to join our team as a Senior Data Engineering Specialist in the Enterprise Architecture & Modernization Fleet to build and evolve data platforms, pipelines, and analytics foundations that power firmwide architecture and modernization metrics. In the Technology division, we leverage innovation to build the connections and capabilities that power our Firm, enabling our clients and colleagues to redefine markets and shape the future of our communities. This is a Lead Data & Analytics Engineering position at Director level, which is part of the job family responsible for providing specialist data analysis and expertise that drive decision‑making and business insights as well as crafting data pipelines, implementing data models, and optimizing data processes for improved data accuracy and accessibility, including applying machine learning and AI‑based techniques. Since 1935, Morgan Stanley is known as a global leader in financial services, always evolving and innovating to better serve our clients and our communities in more than 40 countries around the world. Interested in joining a team that’s eager to create, innovate and make an impact on the world? Read on… What You’ll Do In The Role Provide senior technical leadership and delivery ownership across the Metrics & KPIs squad, supporting multiple enterprise data products spanning architecture metrics, modernization scoring, vendor software analysis, AI adoption, and technology spend transparency. Lead the design, development, and operation of end‑to‑end data pipelines that ingest, validate, transform, and publish datasets from diverse firmwide sources into Snowflake‑based analytical data stores. Design and maintain semantic data models and KPI definitions that enable consistent, trusted measurement across executive dashboards, ad‑hoc analytics, and downstream consumption. Ensure metrics are explainable, reconcilable, and aligned to Technology Strategy objectives. Build and evolve analytics and insight layers using Power BI and Streamlit, delivering executive‑ready dashboards and interactive analytical experiences that emphasize trends, drivers, and decision implications rather than static reporting. Support delivery and integration across the Metrics & KPIs product portfolio, including technology and architecture telemetry ingestion and platform metrics; system and architectural complexity scoring; technology fitness and modernization progress measurement; vendor software technical rating and AI sensitivity analysis; firmwide AI cost, usage, and engagement analytics; and product portfolio, decommissioning, and software spend analytics. Partner closely with Enterprise Architects, Modernization leads, Risk and Resilience teams, and Technology Strategy stakeholders to understand evolving measurement needs and translate them into durable, scalable data solutions. Advance the squad’s roadmap toward predictive and forward‑looking analytics, identifying opportunities where forecasting, trend modeling, simulation, or anomaly detection can materially improve planning, prioritization, and governance. Contribute to engineering standards, development practices, technical documentation, and mentorship within the squad through code reviews, design guidance, and hands‑on leadership. What You’ll Bring To The Role 6+ years of experience as a hands‑on data engineering or analytics engineering practitioner, with sustained ownership of production‑grade, enterprise‑scale data platforms used by senior stakeholders. Demonstrated expertise in advanced SQL and analytical data modeling, including the design and governance of metric‑centric and semantic models that support consistent KPIs across multiple consumption patterns. Significant experience designing, building, and operating data solutions on Snowflake, including ELT‑based architectures, performance optimization, and cost‑aware design for large analytical workloads. Strong proficiency in Python for data engineering and analytics use cases, including pipeline development, data validation, orchestration logic, and analytical workflows. Proven ability to design and operate end‑to‑end data pipelines encompassing ingestion, transformation, validation, metadata enrichment, lineage, and operational monitoring in regulated, reliability‑sensitive environments. Experience establishing and enforcing data quality standards and engineering best practices that materially increase trust in metrics used for executive decision‑making. Experienced in building strong stakeholder partnerships, translating leadership questions into actionable data products and outcomes, and independently prioritizing and leading delivery within a global team using sound technical judgment. Exposure to building analytics and decision‑support applications using AI, Power BI and/or Streamlit, with a focus on insight‑driven narratives rather than static reporting. Preferred exposure to, or strong aptitude for, data science and predictive analytics, such as forecasting, trend modeling, anomaly detection, simulation, or experimentation—particularly when applied to technology or platform telemetry. At Morgan Stanley Montreal, we support the Firm’s global businesses and infrastructure with cutting edge technology and innovation. The multi‑faceted and highly technical Montreal team plays a critical role in building and maintaining our leading technology platform, including electronic trading, algorithm trading, cloud engineering, infrastructure, cybersecurity and AI/ML. Morgan Stanley has been rooted in the Montreal community since 2008 and is considered a leading employer among the area’s highly skilled technology talent. There’s ample opportunity to move across the businesses for those who show passion and grit in their work. All our 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 opportunities employer. We work to provide a supportive and inclusive environment where all individuals can maximize their full potential. 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. For more information, please visit: #J-18808-Ljbffr