Sr. Staff Software Engineer- Eng

Why UKG:  

At UKG, the work you do matters. The code you ship, the decisions you make, and the care you show a customer all add up to real impact. Today, tens of millions of workers start and end their days with our workforce operating platform. Helping people get paid, grow in their careers, and shape the future of their industries. That’s what we do.

We never stop learning. We never stop challenging the norm. We push for better, and we celebrate the wins along the way. Here, you’ll get flexibility that’s real, benefits you can count on, and a team that succeeds together. Because at UKG, your work matters—and so do you.

Job Summary: 

UKG is seeking a highly skilled and experienced engineer to join our Data Platform team. This role requires a self-motivated individual with a deep understanding of Data Warehouse, Near-real time analytics, CDC Eventing Platform and a passion for implementing highly scalable solutions that meet our customers' business needs. The ideal candidate will have a proven track record designing and implementing cloud solutions that support large-scale data operations. They will also have a collaborative attitude, and a strong desire to strive for development standards and efficiencies. The candidate must be able to collaborate with others and successfully leverage their team to deliver on a multitude of project initiatives. Additionally, great organizational and communication skills, a keen sense of process improvement, and a strong desire to solve business problems are essential in this role.   

Duties and Responsibilities:  

• Provide technical leadership and support to UKG Data Platform engineering teams
• Develop and maintain data systems, including but not limited to components for data flow, data storage, data retrieval, communication protocols, security, deployment processes, observability and integration points for high-volume data storage and retrieval across disparate systems.
• Evaluate and choose appropriate programming languages, frameworks, databases, and other technologies based on project needs
• Identify potential bottlenecks and design solutions to measure and optimize system performance and scalability
• Define and enforce CI/CD standards, development methodologies, and quality assurance processes
• Implement security measures to protect sensitive data and prevent vulnerabilities within the system
• Partner with multiple stakeholders to understand requirements and translate those into technical designs 
• Document and communicate design decisions clearly to other developers, provide technical guidance, and resolve technical challenges
• Champion best practices in development, quality, and security while serving as a mentor and fostering a culture of technical excellence and innovation
• Stay abreast of new technologies and industry standards
• Become proficient with our core products and support, educate and lead the group in such discussions

Basic Qualifications:

•  8+ years of software engineering experience, including 3+ years in lead or staff-level positions.
•  Experience architecting enterprise data lakes, lakehouse platforms, or real-time streaming data systems.
•  Strong programming skills in Python, Java, Scala, or similar languages used in data engineering.
•  Deep experience building distributed data systems using GCP services (AWS is also acceptable), including BigQuery, Postgres, AlloyDB, Dataflow (Beam), Dataform, and Pub/Sub.
•  Leverage AI coding agents such as Claude Code or Codex to accelerate software development, including generating production-ready code, refactoring existing systems, debugging complex issues, and improving engineering throughput while maintaining code quality, security, and architectural standards.
•  Experience designing security-first data pipelines with privacy-preserving transformations.
•  Ability to break ambiguous problems into structured designs and actionable plans.
•  Demonstrated ability to mentor engineers and influence technical direction across teams.
•  Strong experience integrating data-science workflows or ML/analytical models into production systems.
•  Strong exposure for highly reliable, scala