Enterprise Data Platform & Operations Leader

Janney Montgomery Scott LLC

Philadelphia (Philadelphia County)

On-site

USD 170,000 - 250,000

Full time

4 days ago

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Benefits offered by this job

Paid Parental Leave

Generous Paid Time Off

Referral bonus

Employee Ownership

Professional Development Assistance

Job summary

Janney Montgomery Scott LLC is seeking an Data Engineering & Operations Leader to drive the enterprise data platform architecture and engineering roadmap. You will oversee data engineering, platform operations, and production support, partnering with Technology, Information Security, and Business leaders to ensure reliability and security across analytics and AI-enabled capabilities.

The role requires 10+ years of leadership in data engineering within financial services, expertise in cloud-based

Qualifications

Bachelor’s degree or higher in a related field.
10+ years leading enterprise data engineering or platform teams in financial services or regulated industries.
Experience designing and modernizing enterprise data platforms using cloud technologies.
Experience leading data engineering teams responsible for data pipelines, integrations, APIs, and production operations.
Strong knowledge of modern data architecture, cloud platforms, DevOps, automation, and data integration.

Responsibilities

Define and execute the enterprise data platform roadmap aligned with strategic priorities and the firm’s technology direction.
Establish architecture principles, engineering standards, and patterns that promote scalability, security, and operational excellence.
Lead evolution and modernization of data platforms, storage, and analytics environments.
Partner with Enterprise Architecture, Technology, and Information Security to align with standards.
Evaluate emerging technologies to improve performance, scalability, and business value while reducing technical debt.
Lead development and operational support of enterprise data pipelines, integrations, and analytical structures.
Oversee production monitoring, incident management, performance, and service reliability.
Implement DevOps, CI/CD, testing, and deployment practices to improve efficiency and quality.
Promote reusable components and standardized engineering practices across Enterprise Data.
Establish a scalable delivery model with internal teams and strategic partners.
Oversee delivery quality, capacity, and performance to meet demand.
Set performance expectations, metrics, and service levels for delivery teams.
Identify opportunities to improve engineering effectiveness and operational efficiency.
Modernize platforms through cloud technologies, automation, and reusable services.