Agile Development Director; Software Engineering Director - Multifamily Technololgy

Position: Agile Development Director (Software Engineering Director) - Multifamily Technololgy
Agile Development Director (Software Engineering Director) - Multifamily Technology

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Position Overview:

We are seeking a highly skilled Software Engineering Director with proven expertise in designing, building, and scaling data solutions. This role requires not only strong technical depth but also the ability to lead, mentor, and inspire teams of data engineers. You will be responsible for driving the technical strategy, design, and implementation of our data platform to enable advanced analytics, AI/ML, and business intelligence across the organization.

This role uniquely combines hands‑on technical leadership with strategic thinking, requiring someone who can design and deliver solutions for today while building capabilities for tomorrow’s AI‑driven landscape.

Our Impact:

The Multifamily Technology supports the multifamily business by crafting and creating solutions to a variety of technology challenges. This support takes many forms, including deploying new technologies such as web‑based solutions driven by AI and microservices, and maintaining critical underwriting and accounting applications.

Your Impact:

• Drive the technical vision for next‑generation applications incorporating AI capabilities.

• Implement responsible AI practices and ensure ethical AI deployments.

• Communicate complex technical ideas clearly and lead teams toward shared goals.

• Lead the adoption of AI‑powered development tools and practices.

• Perform code reviews to ensure code is rigorously designed, elegantly coded, and effectively tuned for performance.

• Balance technical leadership and savvy with strong business judgement to make the right decisions about engineering choices.

• Design solutions that balance innovation with reliability and security.

• Build reusable components and platforms that accelerate development.

• Lead teams to build and integrate Gen AI solutions with enterprise platforms via API‑based methods and standardized patterns.

• Transform how teams approach problem‑solving through AI augmentation.

• Create a culture of technical excellence and continuous innovation.

• Strategically leverage outsourced engineering services to ensure timeliness, scalability, and maintainability of special projects.

Qualifications:

• Bachelor’s or Master’s in Computer Science, Computer Engineering, or related field.

• 15+ years of non‑internship professional experience in software engineering, with at least 5+ years in data engineering.

• 10+ years of experience in design, development, delivery and supporting distributed systems using Java, Spring, Spring Boot, Microservices, RESTful and Graph

QL APIs.

• 4+ years’ experience in developing and maintaining applications using Spark frameworks with strong programming skills in Python, Scala, and the Spark ecosystem.

• Expertise in processing and analyzing large‑scale datasets.

• Knowledge of object‑oriented design, data structures, and algorithms.

• Experience with cloud platforms like AWS, GCP or Azure and their data services.

• Strong knowledge of data fabric concepts (data virtualization, metadata‑driven orchestration, semantic layers).

• Experience with near real‑time data processing, stream‑based integrations, and data serialization formats.

• Experience with data modelling and an understanding of common information models.

• 5+ years’ experience in Agile practices, building software in enterprise environments, with 1+ years in applied Gen AI or LLM‑based solutions.

• Experience with modern data analytics and AI/ML integration (Sage Maker, Tableau, Snowflake Spectrum).

• Hands‑on experience with CI/CD pipelines and modern Dev Ops/Data Ops practices, including Git, Terraform, Jenkins, Pipelines, and containerization.

• Experience in designing, implementing, and maintaining scalable data pipelines and ETL/ELT processes to support enterprise reporting and analytics needs.

• Experience in data governance discipline including master data management, data quality management, metadata management, lineage, and cataloging.

• Experience with OAuth implementation, API management,…