Head of Application Development & Data

Mesirow•Chicago, IL

11d

About The Position

Mesirow is an independent, employee-owned financial services firm founded in 1937. Headquartered in Chicago, with offices around the world, we serve clients through a personal, custom approach to reaching financial goals and acting as a force for social good. With capabilities spanning Private Capital & Currency, Capital Markets & Investment Banking, and Advisory Services, we invest in what matters: our clients, our communities and our culture. We are proud of our employee-owned culture, built on collaboration and shared success, empowering our professionals to develop meaningful relationships, pursue growth opportunities and make a lasting impact for our clients and communities. Mesirow has been named one of the Best Places to Work in Chicago by Crain’s Chicago Business multiple times and is one of Barron’s Top 100 RIA firms. Come join a team that is modernizing all aspects of technology, including custom client-facing applications and the data and AI platforms that power them. The Head of Application Development, Data & AI will serve as a senior technology leader within the Information Technology organization, responsible for driving the firm's application development, data engineering, analytics, and AI strategy. This leader will oversee the evolution of Mesirow's client-facing digital platforms while building scalable data and AI capabilities that enhance client experiences, improve decision-making, and drive operational efficiency across the firm. The successful candidate will be self-motivated and energized by working amongst a diverse group of thoughtful, smart, fast-paced and successful colleagues. The candidate will enjoy being a part of an organization focused on excellence, be a strong team player with a proactive approach, and have the ability to take initiative with discretion and judgment.

Requirements

Azure cloud platform and pipelines
Hybrid Cloud and On Prem
AI/ML platforms and AI agent frameworks applied to analytics and automation
Salesforce platform and vendor ecosystem
Budget forecasting, project planning, and reference architecture reviews
Programming languages: JavaScript, .NET, Python, PowerShell, SQL
Strong understanding of object-oriented and functional programming paradigms and the ability to apply them appropriately.
Experience leading code reviews, architecture reviews, and technical decision-making across multi-stack environments.
Experience implementing and improving SDLC practices, including Agile methodologies, automated testing, CI/CD, and quality assurance processes.
BA/BS Degree in Engineering, Computer Science or a related field.
Industry certifications preferred.
Minimum 10+ years IT experience involving application development and/or data engineering, software development lifecycle, code review, and application support.
Minimum 5 years experience leading application development and/or data engineering teams.
Strong experience across the systems and software development life cycle including design, development, coding, testing and implementation.
Experience with cloud data platforms, data pipelines, and analytics; experience with AI/ML or AI agent solutions strongly preferred.
Understanding of relevant technologies and development life cycles across both applications and data.
Excellent written and oral communication skills, with the ability to effectively communicate and interact with users on all levels.

Nice To Haves

Industry certifications preferred.

Responsibilities

Coach, mentor and manage a team spanning application development and data engineering, including the Data Engineering Manager and their team.
Proven ability to lead a team of IT professionals to deliver solutions on time and to specifications across both application and data domains.
Establish and enforce software security, data governance, architecture, and quality standards across application, analytics, and AI platforms.
Responsible for enforcing coding and data engineering standards and processes — ensuring consistent, well-written, documented, and commented code and pipelines.
Design and manage a combined application and data strategy focused on innovating our technology, while tactically managing and maintaining our applications, data platforms, and analytics for day-to-day operations.
Establish strong working relationships with business members and associated vendor partners.
Create an application, data, and analytics roadmap vision that aligns with business initiatives and goals.
Partner with business leaders to identify strategic opportunities, prioritize investments, and align technology initiatives with firm objectives.
Collaborate with stakeholders to define business requirements, success metrics, and implementation roadmaps for strategic initiatives.
Own the architecture, development, and ongoing evolution of custom client-facing applications, including the client portal.
Support QA by participating in test plan reviews, attending triage meetings, and guiding bug fixes.
Establish application architecture standards and ensure alignment with enterprise technology strategy.
Drive modernization efforts including cloud-native architectures, API strategies, automation, and platform scalability.
Execute code review and architectural decision-making within a multi-stack environment.
Mature our SDLC process, including agile-light and unit testing practices.
Lead the enterprise adoption of AI, generative AI, and intelligent agents by identifying high-value business use cases, establishing reusable AI platforms, and delivering measurable improvements in productivity, automation, analytics, and client experience.
Partner with business leaders to identify and prioritize AI opportunities that improve advisor productivity, client service, operational efficiency, and decision-making while ensuring compliance, security, and regulatory alignment.
Lead the Azure-based data engineering/analytics function, including pipeline development, data migration, and integration efforts.
Own the design and management of the firm's data platform, including Databricks, Azure Data Factory and associated cost optimization.
Evaluate emerging technologies and industry trends to identify opportunities for innovation and competitive advantage.
Direct the analytics capability that turns firm and client data into actionable insight for the business.
Establish governance, security, and quality standards for data and AI initiatives, balancing innovation with risk management.