VP, Workplace Automation Lead (Power Platform)

Jefferies•Jersey City, NJ

2h•Onsite

About The Position

The Vice President, Workplace Automation & Analytics is a senior technical leader responsible for designing and building enterprise automation and analytics solutions on modern cloud and data platforms. This role blends hands-on software development with solution architecture, delivering high-impact business automation and data products on a scale. Working across Microsoft-centric technology stacks, the VP serves primarily as an individual contributor with broad architectural authority, while providing technical leadership and guidance to global teams through a Center of Excellence model. The focus is on coding, architecting, and deploying robust solutions that accelerate productivity and insights across Jefferies.

Requirements

5+ years of deep, hands-on experience delivering enterprise-scale solutions using Microsoft Power Platform, including Power Apps, Power Automate, Power BI, and Copilot Studio
Proven ability to extend Power Platform solutions with custom code, APIs, Azure Functions, and cloud services in production environments
Demonstrated experience designing and governing enterprise Power Platform environments, including security, data access, and application lifecycle management
Proven experience delivering AI-enabled automation or analytics solutions into production, not limited to proofs of concept
Hands-on experience integrating AI or machine learning capabilities into workflows, applications, or analytics platforms
Practical experience with Azure AI services, Azure OpenAI, or equivalent enterprise AI platforms, with clear business impact
10+ years of experience in software engineering, data engineering, or solution architecture, including 5+ years at a senior or principal technical level
Strong hands-on coding expertise in Python and advanced SQL for automation, services, and data pipelines
Proven experience designing and delivering enterprise data pipelines, ETL/ELT processes, and business-facing analytics solutions
Strong experience delivering analytics using Power BI, including semantic models and DAX
Strong hands-on experience with Microsoft Azure, including serverless services, identity, security, and cloud-native architectures
Proven ability to partner with business stakeholders to gather requirements, propose technical solutions, manage delivery expectations, and provide clear status and outcome updates
Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or equivalent hands-on industry experience

Responsibilities

Design and develop high-quality automation applications, data pipelines, and analytics solutions using enterprise platforms.
Write code (e.g., Python, SQL) and build frameworks to implement scalable workflows, data integrations, and APIs that meet complex business requirements.
Provide architectural direction on system design, integration patterns, and cloud infrastructure.
Apply a strong data engineering and data science background to create and optimize data models, ETL processes, and analytical features.
Develop pipelines and data integrations across cloud services (e.g., Azure) to incorporate data from multiple sources into unified analytics solutions (Power BI dashboards, Fabric-style unified data environment).
Enable advanced analytics and machine learning use cases by collaborating with data scientists and implementing necessary data pipelines.
Lead end-to-end development of solutions that leverage Microsoft Power Platform (Power Apps, Power Automate, Power BI, Copilot Studio) and Azure cloud services.
Implement best practices in cloud-native development, including microservices architecture, serverless computing (like Azure Functions), and secure API development.
Champion the use of CICD pipelines and DevOps tooling to streamline deployments and ensure quality, reliability, and performance of production systems.
Serve as a technical authority and mentor, guiding teams and “citizen developers” in adopting best practices, coding standards, and solution design patterns.
Review code and architecture designs to ensure solutions are robust, resilient, and adhere to enterprise standards.
Collaborate closely with cross-functional stakeholders (engineering teams, business analysts, QA, etc.) to align technical solutions with business needs and operational considerations.
Drive innovation in enterprise automation and analytics, researching emerging technologies (AI, advanced analytics, cloud services) and evaluating their applicability.
Lead proof-of-concept initiatives to introduce new capabilities (e.g., incorporate AI/ML models into workflows).
Continuously improve processes, tools, and frameworks to accelerate development, reduce technical debt, and enhance system performance.