Lead Data Engineer (Python, Databricks, SQL)

CIBC•Chicago, IL

9d•Hybrid

About The Position

The Lead Data Engineer will own end-to-end delivery of U.S. Data Strategy capabilities, including ETL, analytics, and data consumption, aligned to a multi-year product roadmap. They will translate business and product objectives into secure, scalable cloud data solutions in partnership with Product, Architecture, Data, and key stakeholders. Continuously improve SDLC throughput via intake/estimation and KPI management, and drive innovation through proofs of concept and continuous modernization. This is a hands-on position. CIBC we enable the work environment most optimal for you to thrive in your role. You’ll have the flexibility to manage your work activities within a hybrid work arrangement where you’ll spend 2 days per week on-site, while other days may be remote.

Requirements

8-12 years of related experience OR Combination of education and experience, ideally within financial services or tech.
Azure/Databricks data engineering expertise (PySpark/Scala, ETL, Azure SQL, REST APIs).
Expertise in data ingestions, data pipeline development, and optimization, reporting, and advanced analytics using Azure and Databricks (Pyspark/Scala) services and/or SQL Server/SSIS is a must.
Strong SQL Server development experience (required) and SSIS (desired) along with strong pipeline delivery skills (ingestion, transformation, optimization, reporting/analytics).
DevOps/SDLC excellence (CI/CD, environment integrity, security, compliance, release management).
Agile delivery mastery (Jira/Azure DevOps, story writing/pointing, velocity management).
Executive-level communication for technical recommendations and governance forums.
Degree/diploma in Computer Science, Engineering, MIS, or related field or relevant certifications and/or completion of a relevant bootcamp.
You need to be legally eligible to work at the location(s) specified above and, where applicable, must have a valid work or study permit.

Nice To Haves

Exposure to Integration and BI Tools such as Tableau, Cognos or Power BI.
Automation mindset to reduce manual processes and improve operational efficiency is desired.
Extensive knowledge of banking products (desired), services, and industry regulations; expert understanding of current industry trends and developments; ability to influence strategic decisions using industry knowledge.

Responsibilities

Own end-to-end delivery of U.S. Data Strategy capabilities, including ETL, analytics, and data consumption, aligned to a multi-year product roadmap.
Translate business and product objectives into secure, scalable cloud data solutions in partnership with Product, Architecture, Data, and key stakeholders.
Continuously improve SDLC throughput via intake/estimation and KPI management, and drive innovation through proofs of concept and continuous modernization.
Set goals aligned to strategy; translate priorities into roadmaps, metrics, dependencies, and release plans; manage capacity and resourcing.
Leverage GitHub Copilot in development best practices.
Define secure, scalable architecture; modernize and reduce technical debt.
Drive best practice engineering through automation, testing, CI/CD, observability, and continuous improvement.
Apply banking/domain expertise to guide platform direction and improve client and operational outcomes.
Embed risk management and security/privacy by design; ensure regulatory compliance and partner with Compliance/Audit.
Oversee risk management activities within their area, influence risk culture, and align risk management with departmental goals.
Oversee compliance adherence within their area of responsibility; ensure alignment with regulatory requirements; engage with Compliance and Audit teams as needed.
Provide Technical Leadership, be able to develop solutions based on Databricks/Python/PySpark as well as strong SQL Server experience.