Lead Data Engineer, Applied AI Data Ingestion & Integration
Core
Lead the analysis, profiling, integration, quality assessment, and operationalization of structured, semi-structured, and unstructured data for AI, machine learning, and Generative AI applications.
Role type
Lead Data Engineer (Applied AI Data Ingestion & Integration)
Builds
Scalable data ingestion and integration pipelines, AI-ready datasets, multimodal document ingestion pipelines, and RAG solutions.
Domain
Financial Services / Banking / AI Data Engineering
Deliverable
production ML models | product features
Required skills
SQL, Python, enterprise data integration, data warehousing, ETL/ELT, cloud data platforms, data governance, data lineage, metadata management, vector databases, RAG evaluation, MLOps, CI/CD, stakeholder management, technical leadership, mentoring
Preferred skills
Financial services domain knowledge, Responsible AI frameworks (SR 11-7, OSFI E-23), Master's degree, cloud certifications
Technologies
Azure Data Factory, Azure AI Search, Power BI, Tableau, REST APIs, JSON/XML
Responsibilities
Design and implement reliable, scalable data ingestion pipelines for multi-modal data; Establish and monitor data quality standards and controls; Collaborate with AI teams to prepare and optimize datasets for ML and GenAI; Lead cross-functional initiatives from discovery through production; Mentor junior team members and drive continuous improvement.
Seniority
Senior, hands-on IC with leadership responsibilities