# Senior Manager, Data Engineering, Applied AI Data Ingestion & Integration (DII) Source: https://realanalystjobs.com/job/senior-manager-data-engineering-applied-ai-data-ingestion-and-integration-dii-ba-c15521ec Senior Manager, Data Engineering, Applied AI Data Ingestion & Integration (DII) at Bank of Montreal, an on-site role based in Chicago, Illinois, USA. Experience level: 8-10 Years. Posted on 29 October 2026, read from Bank of Montreal's own careers page (Workday), which RealAnalystJobs re-checks daily and removes the role when it closes. Bank of Montreal has approved H-1B petitions on USCIS record (employer-wide, not a promise for this role). Updated 15 November 2026. ## Key facts - Company: [Bank of Montreal](https://realanalystjobs.com/companies/bank-of-montreal) - Location: Chicago, Illinois, USA - Work mode: On-site - Posted: Oct 29, 2026 - Employment type: Full time - Experience level: 8-10 Years - Source: Bank of Montreal's careers page (Workday), re-checked daily Skills: [SQL](https://realanalystjobs.com/skills/sql), [Python](https://realanalystjobs.com/skills/python), [Tableau](https://realanalystjobs.com/skills/tableau), [Power BI](https://realanalystjobs.com/skills/power-bi), Azure ## Visa sponsorship The posting does not say. Bank of Montreal had H-1B petitions approved for 16 workers in fiscal year 2026 (USCIS). That is history, not a promise for this role. [See the record](https://realanalystjobs.com/companies/bank-of-montreal#h1b-record) ## About this role Application Deadline: 11/29/2026 Address: 320 S Canal Street Job Family Group: Data Analytics & Reporting Please note this role is Individual Contributor (Senior Manager level) and HYBRID Team Overview We accelerate BMO’s AI journey by building enterprise-grade, cloud-native capabilities and AI solutions. Our team combines engineering excellence with cutting-edge AI to deliver scalable, secure, and responsible solutions that power business innovation across the bank. We are engineers, AI practitioners, platform builders, thought leaders, multipliers, and coders. Above all, we are a global team of diverse individuals who enjoy working together to create smart, secure, and scalable solutions that make an impact across the enterprise. The Applied AI Data Ingestion & Integration (DII) team provides end‑to‑end services to help move, prepare, and operationalize data for AI and analytics workloads. As a Senior Manager within the (DII) Team, you will play a key role in enabling BMO's AI and advanced analytics capabilities by transforming complex business requirements into scalable data solutions. You will lead the analysis, profiling, integration, quality assessment, and operationalization of structured, semi-structured, and unstructured data used across AI, machine learning, and Generative AI applications. This position involves close collaboration with various technology teams, Cross POD leads, Data Engineers, Data Scientists, Architects, AI and Data engineers, and Business stakeholders to push the adoption of Generative AI technologies and agentic flows across enterprise-wide applications and processes, and to develop partnerships with third-party providers for validating and adopting production-grade solutions. Your work will directly support the development of AI-ready datasets, multimodal document ingestion pipelines, Retrieval-Augmented Generation (RAG) solutions, Building various connectors, resources, and tools for (Model Context Protocol) MCPs. This role requires deep technical expertise, strong engineering judgement, and the ability to lead through influence. The successful candidate will be expected to own technical outcomes, mentor engineers, manage ambiguity, and drive measurable improvements in platform capability, delivery quality, operational resilience, and business value. Key Responsibilities: Data Analysis & Integration Leadership • Deep hands-on technical leadership with enterprise data onboarding, ingestion, and integration initiatives supporting AI, analytics, and business intelligence use cases. • Lead and partner with Product Owners, Data Engineers, Data Scientists, and business stakeholders to translate business needs into actionable data requirements, data models, and integration strategies. • Design and implement reliable, scalable data ingestion and integration pipelines for structured, semi-structured, unstructured data (e.g., databases, files, documents, APIs, events), and multi-modal data, ensuring data is AI ready, governed, secure, and observable. • Ensure pipelines follow enterprise governance, access control, and security standards, including role-based access and lineage considerations. Monitor pipeline performance, troubleshoot failures, and optimize cost and throughput. • Document processes, share knowledge, and contribute to a culture of continuous learning and responsible innovation. Data Quality, Governance & Compliance • Establish and monitor data quality standards, controls, and metrics to ensure accuracy, completeness, timeliness, and consistency. • Partner with Data Governance, Risk, Compliance, and Model Risk Management teams to ensure adherence to enterprise data policies, regulatory requirements, and Responsible AI standards. • Support data lineage, metadata management, data cataloging, and traceability capabilities across ingestion and integration platforms. AI & Advanced Analytics Enablement • Collaborate with AI and Data Science teams to prepare, validate, and optimize datasets for machine learning, Generative AI, and advanced analytics applications. • Support multimodal data ingestion initiatives involving documents, images, audio, video, and enterprise knowledge repositories. • Analyze performance and effectiveness of chunking, indexing, retrieval, and data preparation strategies used in RAG and AI Search solutions. • Develop production‑grade services and AI capabilities using Python, REST APIS, JSON/XML, vector databases, RAG evaluation and retrieval metrics. • Develop analytical frameworks and KPIs to measure data platform effectiveness, ingestion performance, quality trends, and business outcomes. • Evaluate emerging AI and data management technologies and recommend opportunities to improve DII capabilities. Stakeholder Management & Leadership • Lead cross-functional initiatives from discovery through production, partnering with business, technology, architecture, risk, security, and operations teams. • Provide mentorship and guidance to analysts and junior team members, fostering a culture of continuous learning and analytical excellence and technical accountability. • Communicate complex technical findings, risks, and recommendations to both technical and non-technical audiences, including senior leadership. • Own and drive continuous improvement initiatives that increase automation, operational efficiency, and scalability of data ingestion and integration processes. Required Qualifications: • 8-10 years of experience in Data Engineering/ support, or related analytics disciplines, preferably within large enterprise environments. • 3+ years experience as a Technical Delivery leader (driving and owning the work) • Demonstrated experience in leading technical delivery for enterprise data integration, data warehousing, ETL/ELT processes, cloud data platforms, data governance, and production analytics or AI platforms. • Strong proficiency in SQL, Python, or similar, and experience working with large-scal Description from Bank of Montreal's public careers feed, reproduced so you can read the role here. Apply on the company's own site; Real Analyst Jobs never submits anything for you. ## How to apply Open [this role on Real Analyst Jobs](https://realanalystjobs.com/job/senior-manager-data-engineering-applied-ai-data-ingestion-and-integration-dii-ba-c15521ec) and use Apply now there to reach the employer's application. The listing is re-checked against Bank of Montreal's careers page daily and removed when it closes. ## Bank of Montreal 15 open analyst roles on Real Analyst Jobs. [More roles at Bank of Montreal](https://realanalystjobs.com/companies/bank-of-montreal) ## More like this ### Other open roles at Bank of Montreal - [Senior Business Analyst, Commercial Risk Data](https://realanalystjobs.com/job/senior-business-analyst-commercial-risk-data-bank-of-montreal-ade6155f), Toronto, Canada (On-site) - [ServiceNow Technology Lifecycle Analyst](https://realanalystjobs.com/job/servicenow-technology-lifecycle-analyst-bank-of-montreal-bd316811), Toronto, Canada (On-site) - [Senior Analyst, Wealth Data Foundations](https://realanalystjobs.com/job/senior-analyst-wealth-data-foundations-bank-of-montreal-ca391f42), Toronto, Canada (On-site) - [Senior Analyst Data Analytics](https://realanalystjobs.com/job/senior-analyst-data-analytics-bank-of-montreal-2db3320b), Toronto, Canada (On-site) - [Associate, Portfolio Analytics](https://realanalystjobs.com/job/associate-portfolio-analytics-bank-of-montreal-2843848a), Toronto, Canada (On-site) - [Data analyst jobs in the USA](https://realanalystjobs.com/jobs/data-analyst-jobs-in-usa) - [Analyst job market report](https://realanalystjobs.com/analyst-job-market) - [What analyst roles pay](https://realanalystjobs.com/blog/data-analyst-salaries) ## Sources and links - [This role on Real Analyst Jobs](https://realanalystjobs.com/job/senior-manager-data-engineering-applied-ai-data-ingestion-and-integration-dii-ba-c15521ec) - [Bank of Montreal on Real Analyst Jobs](https://realanalystjobs.com/companies/bank-of-montreal) - [All analyst jobs](https://realanalystjobs.com/jobs)