Assistant Director, Software Engineering

Northwestern Mutual•Milwaukee, WI

11d•Hybrid

About The Position

We are seeking an experienced and technically strong Assistant Director to lead execution, delivery, and evolution of the Data De-Identification (DDI) initiative, a critical component of our broader Testing Transformation strategy. This role requires a deeply technical and hands-on engineering leader with experience designing and delivering data de-identification solutions, including techniques such as data masking, truncation, tokenization, synthetic data generation, data scanning, and remediation. The Assistant Director will be responsible for applying these techniques at scale across complex enterprise systems to ensure secure and compliant handling of sensitive data. Reporting to the Senior Director, this role is responsible for driving day-to-day engineering leadership, technical direction, and roadmap execution for DDI solutions. The Assistant Director will lead a team of engineers and vendor partners to build scalable, secure, and high-impact solutions that improve how sensitive data is handled across prevent, detect, and remediate pillars. This role requires a hands-on technical leader who has practical experience working on similar data protection, privacy, or de-identification initiatives, with the ability to navigate complex data ecosystems and influence enterprise-wide adoption.

Requirements

Proven experience working on data de-identification, data privacy, or sensitive data management initiatives
Strong understanding of: Data masking and obfuscation techniques, Synthetic data generation approaches, Data discovery, classification, and scanning tools, Data remediation and compliance workflows
Strong understanding of SDLC and modern engineering practices
Solid data engineering knowledge, including how data flows across systems and environments
Proven ability to make sound technical decisions and guide architecture/design
Experience working with public cloud and on-prem application architectures
Familiarity with databases and platforms such as: Aurora/RDS, Postgres, DB2, DynamoDB, Databricks, MySQL, Sybase
Strong understanding of design patterns, distributed systems, and data security practices
Execution & Vendor Management: Demonstrated success in delivering outcomes through vendor partners and hybrid teams
Ability to manage multiple priorities, teams, and dependencies effectively
Strong communication skills with the ability to engage both technical and non-technical stakeholders
Ability to influence teams and leaders on important technical and business decisions
Comfortable operating with visibility across leadership levels
Bachelor's Degree or equivalent experience.
8–12 years of professional experience in software engineering, data engineering, or related fields
3-5+ years of experience working with modern engineering tools, languages and practices.
4–8+ years leading engineering teams, including Software Engineering, DevOps, or Data Engineering including: Growing engineering skill sets in others. Developing future engineering leaders. Providing direct feedback and performance reviews.
Proven track record of successfully designing and delivering significant and impactful technology solutions.
Experience developing and leading solution delivery using agile methods.
Solid understanding of the organizations primary domains and business functions.
Capable of communicating between product, engineering, and the business.
Ability to successfully communicate to both technical and non-technical audiences in varying forms and levels of detail.
Leads the team to collaboration.

Responsibilities

Lead, coach, and develop a high-performing team of engineers, fostering accountability, technical excellence, and continuous improvement.
Own end-to-end delivery of DDI solutions, ensuring timely execution against roadmap commitments such as Data masking, Data truncation, Synthetic data generation, Data scanning and discovery and Data remediation workflows
Drive a strong execution culture, ensuring work is prioritized, tracked, and delivered with quality and predictability.
Actively remove blockers and ensure teams are focused on delivering outcomes.
Define and create new technical solutions to address complex business and engineering challenges within the DDI domain.
Pull together key technical SMEs (data, platform, security, application teams) to evaluate solution options, align on architecture, and drive execution.
Drive alignment and progress despite constraints (technical, organizational, or operational) to ensure successful delivery of results.
Serve as a hands-on technical leader, capable of diving deep into architecture, design, and implementation.
Make and drive key technical decisions aligned with enterprise architecture and long-term scalability goals.
Review and guide system design, data flows, and integration patterns across applications.
Ensure adherence to engineering best practices, design patterns, and data protection standards.
Partner closely with Product, Program, and Business stakeholders to define and execute the DDI roadmap.
Translate business strategy into clear technical plans, priorities, and deliverables.
Ensure DDI solutions to integrate seamlessly into the broader developer workflow, test environments, and automation ecosystem.
Continuously evaluate and refine roadmap based on business needs, technical insights, and outcomes.
Lead delivery through a mix of internal teams and vendor partners.
Demonstrate a proven ability to get work done through vendor resources, ensuring accountability, quality, and delivery outcomes.
Establish clear expectations, operating models, and performance metrics for vendors.
Actively manage vendor relationships to optimize cost, productivity, and results.
Collaborate across engineering, platform, security, and business teams to align solutions with enterprise needs.
Drive enterprise adoption of de-identified and synthetic data patterns, influencing teams to shift toward secure and compliant data practices.
Work closely with Testing Transformation teams to drive alignment across test data, environments, tooling, and automation.
Influence decisions and drive alignment across multiple stakeholders and teams.
Implement and improve engineering processes, SDLC practices, and delivery frameworks.
Ensure high standards for product quality, reliability, and performance.
Drive continuous improvement in development, deployment, and operational practices.
Hire, develop, and retain top engineering talent.
Provide direct feedback, mentorship, and performance evaluations.
Build strong technical capabilities within the team and develop future engineering leaders.