Lead Data Engineer, Applied AI Data Ingestion

BMO Harris Bank

Chicago (IL)

On-site

USD 122,000 - 228,000

Full time

8 days ago

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Benefits offered by this job

Health insurance
Tuition reimbursement
Accident and life insurance
Retirement savings plans

Job summary

BMO Financial Group is seeking a Lead Data Engineer for the Applied AI Data Ingestion & Integration team to advance AI data pipelines across the enterprise. You will own data ingestion, transformation, quality, and governance, collaborating with data scientists, developers, and product stakeholders to deliver scalable, secure AI-ready datasets.

The role demands deep technical expertise, leadership by influence, and a track record of delivering production-grade data solutions in financial

Qualifications

  • 8-10 years of experience in Data Engineering or related analytics.
  • 3+ years in technical delivery leadership.
  • Experience in enterprise data integration, data warehousing, ETL/ELT, cloud data platforms.

Responsibilities

  • Lead data onboarding, ingestion, and integration initiatives supporting AI and analytics use cases.
  • Translate business needs into data requirements, models, and integration strategies.
  • Design reliable, scalable data pipelines for structured and unstructured data.
  • Ensure governance, security, and observability of pipelines.
  • Mentor engineers and drive improvements in data platform capabilities.

Skills

SQL
Python
Power BI
Tableau
Azure Data Factory
Azure AI Search
MLOps
Cloud data platforms

Education

Bachelor's degree in computer science or related field
Master's degree in data science or related field (preferred)
Certifications in Data Management / Cloud Platforms (asset)

Tools

REST APIs

Job description

BMO Financial Group is seeking a Lead Data Engineer for the Applied AI Data Ingestion & Integration team to advance AI data pipelines across the enterprise. You will own data ingestion, transformation, quality, and governance, collaborating with data scientists, developers, and product stakeholders to deliver scalable, secure AI-ready datasets.

The role demands deep technical expertise, leadership by influence, and a track record of delivering production-grade data solutions in financial

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