Sr. Staff Software Engineer- Data

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 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, scalable, secure, and decoupled solution Strong exposure of Continuous Integration and Continuous Delivery process (CI/CD) Excellent leadership, communication, and interpersonal skills, with the ability to influence and collaborate with stakeholders at all levels of the organization. Understanding of data modeling, partitioning strategies, schema evolution, and cost-efficient query optimization. Experience working with large-scale structured and unstructured datasets in cloud-based environments. Experience improving platform reliability through observability, data quality frameworks, and automated validation techniques. Experience operating in regulated environments with strong data compliance and audit requirements.