Senior Manager, Data Engineer, Applied AI Data Ingestion & Integration
BMO Financial Group10 days ago
Toronto, CanadaStaff+
Base Salary
$105k - $215k/yr
Responsibilities
- Lead enterprise data onboarding, ingestion, integration, and technical delivery initiatives for AI, analytics, and business intelligence use cases.
- Translate business needs into data requirements, data models, and integration strategies with product, engineering, data science, and business stakeholders.
- Design and implement scalable ingestion and integration pipelines for structured, semi-structured, unstructured, and multimodal data.
- Ensure pipelines meet governance, access control, security, lineage, observability, and responsible AI standards.
- Monitor pipeline performance, troubleshoot failures, and optimize cost, throughput, automation, and operational resilience.
- Establish and monitor data quality standards, controls, metrics, metadata, cataloging, and traceability.
- Prepare and validate datasets for machine learning, Generative AI, advanced analytics, AI Search, and RAG applications.
- Develop production-grade services and AI capabilities using Python, REST APIs, JSON/XML, vector databases, and retrieval evaluation metrics.
- Develop analytical frameworks and KPIs for platform effectiveness, ingestion performance, quality trends, and business outcomes.
- Lead cross-functional initiatives from discovery through production and communicate technical findings and recommendations to technical and non-technical audiences.
- Mentor analysts and junior team members and drive continuous learning, technical accountability, and responsible innovation.
Requirements
- Bachelor’s degree in computer science, information systems, data analytics, statistics, engineering, mathematics, business analytics, or a related quantitative field.
- 8–10 years of experience in data engineering, data engineering support, or related analytics disciplines, preferably in large enterprise environments.
- At least 3 years of experience as a Technical Delivery Leader who owned the work.
- Experience leading enterprise data integration, data warehousing, ETL/ELT, cloud data platforms, data governance, and production analytics or AI platforms.
- Strong proficiency in SQL, Python, or similar technologies and experience with large-scale datasets across cloud and on-premises environments.
- Experience with Power BI, Tableau, Python, Azure Data Factory, Azure AI Search, or equivalent technologies.
- Strong communication, stakeholder management, prioritization, initiative leadership, and delivery skills in highly regulated environments.
- Familiarity with MLOps, CI/CD, and cloud-based AI infrastructure.
- Knowledge of Agile delivery methodologies and experience working in cross-functional product teams.
- Experience in financial services, banking, risk, compliance, or another highly regulated industry is preferred.
- Knowledge of Responsible AI, Model Risk Management, SR 11-7, OSFI E-23, or related governance frameworks is preferred.
- A master’s degree in data science, analytics, computer science, information management, business administration, or a related field is preferred.
- Relevant certifications in data management, cloud platforms, analytics, AI, or data governance are an asset.
Benefits
- Hybrid work arrangement.
- Health insurance, tuition reimbursement, accident and life insurance, and retirement savings plans.
- Training, coaching, manager support, and network-building opportunities.
- Inclusive, equitable, and accessible workplace with accommodations available on request.
About BMO Financial Group
BMO Financial Group is a publicly traded North American bank offering personal and commercial banking, wealth management, and capital markets services to consumers, businesses, and institutions. Founded in 1817 and headquartered in Toronto, it operates in Canada and the United States, including BMO Bank N.A. in the U.S. The company is listed on the NYSE and TSX under the symbol BMO.