Senior Manager, Data Engineer, Applied AI Data Ingestion & Integration

Role Overview

Data Integration Leadership

• Lead enterprise data onboarding, ingestion, and integration 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 scalable pipelines for databases, files, documents, APIs, events, and multimodal data.
• Ensure pipelines meet governance, access control, security, lineage, observability, cost, and throughput expectations.

Data Quality and Governance

• Establish and monitor data quality standards, controls, and metrics for accuracy, completeness, timeliness, and consistency.
• Partner with governance, risk, compliance, and model risk teams on enterprise policies, regulations, and Responsible AI standards.
• Support data lineage, metadata management, data cataloging, and traceability across ingestion and integration platforms.

AI Enablement

• Prepare, validate, and optimize datasets for machine learning, Generative AI, and advanced analytics applications.
• Support ingestion of documents, images, audio, video, and enterprise knowledge repositories.
• Analyze chunking, indexing, retrieval, and data preparation strategies for RAG and AI Search solutions.
• Develop production-grade services using Python, REST APIs, JSON/XML, vector databases, and retrieval metrics.

Stakeholder Leadership

• Lead cross-functional initiatives from discovery through production with business, technology, architecture, risk, security, and operations teams.
• Communicate technical findings, risks, and recommendations to technical and non-technical audiences, including senior leadership.
• Mentor analysts and junior team members and drive automation, operational efficiency, and scalability improvements.

Qualifications

• 8-10 years of experience in data engineering, data engineering support, or related analytics disciplines, preferably in large enterprises.
• At least 3 years of experience as a technical delivery leader who owned the work.
• Experience with enterprise data integration, data warehousing, ETL/ELT, cloud data platforms, governance, and production analytics or AI platforms.
• Strong proficiency in SQL, Python, or a similar technology and experience with large-scale datasets across cloud and on-premises environments.
• Familiarity with MLOps, CI/CD, cloud-based AI infrastructure, and Agile delivery methodologies.
• Bachelor’s degree in a quantitative, technology, engineering, or related field is required.
• A master’s degree and relevant data, cloud, analytics, AI, or governance certifications are preferred or considered assets.

Compensation

• The stated salary range is $105,000 to $215,000.
• The position is salaried, with compensation varying according to location, skills, experience, education, and qualifications.

Workplace

• This is explicitly identified as a hybrid role.

About the Employer